FreeCourseSite com Udemy Complete Data Science Machine Learning DL NLP Bootcamp

FreeCourseSite com Udemy Complete Data Science Machine Learning DL NLP Bootcamp

Name	[FreeCourseSite.com] Udemy - Complete Data Science,Machine Learning,DL,NLP Bootcamp	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	75.8 GB
Total Files	1178
Last Seen	2025-06-27 00:07
Hash	F3C52D58434E45630FA17D2E2CBBCD89B8F744DD

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/01 - Getting Started/
001 Welcome To The Course.mp4	59.4 MB
001 Welcome To The Course_en.srt	4.5 KB
002 Complete Materials.html	0.4 KB
003 Anaconda Installation.mp4	129.0 MB
003 Anaconda Installation_en.srt	21.0 KB
004 Getting Started With VS Code.mp4	142.7 MB
004 Getting Started With VS Code_en.srt	22.6 KB
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/02 - Python Programming Language/
001 Getting Started With VS Code.mp4	38.6 MB
001 Getting Started With VS Code_en.srt	19.4 KB
002 Different Ways of Creating Virtual Environment.mp4	87.1 MB
002 Different Ways of Creating Virtual Environment_en.srt	13.9 KB
003 Solve Conda Not Recognized Isssue.html	0.3 KB
004 Python Basics-Syntax And Semantics.mp4	143.5 MB
004 Python Basics-Syntax And Semantics_en.srt	33.9 KB
005 Variables In Python.mp4	92.4 MB
005 Variables In Python_en.srt	34.8 KB
006 Basics Data Types In Python.mp4	78.0 MB
006 Basics Data Types In Python_en.srt	17.8 KB
007 Operators In Python.mp4	173.8 MB
007 Operators In Python_en.srt	28.0 KB
008 Coding Excercise And Assignments.html	0.2 KB
008 assignment-solution.zip	3.3 KB
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/03 - Python Control Flow/
001 Conditional Statements (if, elif, else).mp4	326.2 MB
001 Conditional Statements (if, elif, else)_en.srt	35.0 KB
002 Loops In Python.mp4	321.2 MB
002 Loops In Python_en.srt	50.5 KB
003 Coding Excercise And Assignments.html	0.2 KB
003 assignment-solutions.zip	2.7 KB
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/04 - Inbuilt Data Structures In Python/
001 List And List Comprehension In Python.mp4	207.7 MB
001 List And List Comprehension In Python_en.srt	63.9 KB
002 List Practice Code And Assignment.html	0.2 KB
002 list-assignment-solution.zip	3.6 KB
003 Tuple In Python.mp4	82.4 MB
003 Tuple In Python_en.srt	40.5 KB
004 Tuple Assignment And Practise Code.html	0.2 KB
004 tuple-assignment-solution.zip	2.9 KB
005 Sets In Python.mp4	207.2 MB
005 Sets In Python_en.srt	38.8 KB
006 Sets Assignment and Practise Code.html	0.2 KB
006 set-assignments-solution.zip	2.9 KB
007 Dictionaries In Python.mp4	216.7 MB
007 Dictionaries In Python_en.srt	61.3 KB
008 Dictionaries Assignments And Practise Questions.html	0.2 KB
008 dictionaries-assignment.zip	3.2 KB
009 Real world Usecases Of List.mp4	39.6 MB
009 Real world Usecases Of List_en.srt	17.9 KB
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/05 - Functions In Python/
001 Getting Started With Functions.mp4	87.6 MB
001 Getting Started With Functions_en.srt	41.3 KB
002 More Coding Example With Functions.mp4	198.6 MB
002 More Coding Example With Functions_en.srt	49.4 KB
003 Lambda Function In Python.mp4	60.8 MB
003 Lambda Function In Python_en.srt	18.2 KB
004 Map Function In Python.mp4	60.3 MB
004 Map Function In Python_en.srt	19.9 KB
005 Filter Function In Python.mp4	50.9 MB
005 Filter Function In Python_en.srt	15.7 KB
006 Functions Assignments and Practise Content.html	0.1 KB
006 advancefunctions.zip	4.5 KB
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/06 - Function Practice Question/
001 Celsius To Fahrenheit.html	5.8 KB
002 Area of a Rectangle.html	5.7 KB
003 Distance Covered by a Vehicle.html	5.8 KB
004 Number of Rounds of Lift.html	6.2 KB
005 Line Equation.html	5.8 KB
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/07 - Inbuilt Data Structure - Practice Question/
001 Sum of List Elements.html	6.0 KB
002 Largest Element in a List.html	6.6 KB
003 Remove Duplicate in a List.html	6.3 KB
004 Check if all elements in a List are Unique.html	6.1 KB
005 Reverse a List.html	6.0 KB
006 Number of Odd and Even Elements in a list.html	6.2 KB
007 Check if List is Subset of Another List.html	6.7 KB
008 Maximum Difference between 2 consecutive elements in a List.html	6.7 KB
009 Merge two sorted List.html	7.0 KB
010 Rotate a List.html	6.5 KB
011 Merge 2 list into Dictionary.html	6.7 KB
012 Merge Multiple Dictionary.html	6.6 KB
013 Words Frequency in a Sentence.html	6.8 KB
014 Palindromic Tuple.html	7.1 KB
015 Merge Dictionaries with Common Keys.html	7.2 KB
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/08 - Importing Creating Modules And Packages/
001 Import Modules And Packages In Python.mp4	55.5 MB
001 Import Modules And Packages In Python_en.srt	31.3 KB
002 Standard Library Overview.mp4	146.6 MB
002 Standard Library Overview_en.srt	31.4 KB
003 Packages Assignment And Practise Questions With Solutions.html	0.1 KB
003 packagessolution.zip	3.6 KB
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/09 - File Handling In Python/
001 File Operation In Python.mp4	137.4 MB
001 File Operation In Python_en.srt	30.5 KB
002 Working With File Paths.mp4	52.6 MB
002 Working With File Paths_en.srt	13.9 KB
003 File handling Operation Assignment With Solutions.html	0.1 KB
003 filehandlingquestions.zip	3.3 KB
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/10 - Exception Handling In Python/
001 Exception Handling With try except else and finally blocks.mp4	146.7 MB
001 Exception Handling With try except else and finally blocks_en.srt	46.2 KB
002 Exception Handling Practise Assignments And Solution.html	0.1 KB
002 exceptionhandlingsolution.zip	4.2 KB
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/11 - OOPS Concepts With Classes And Objects/
001 Classes And Objects In Python.mp4	87.7 MB
001 Classes And Objects In Python_en.srt	40.4 KB
002 Classes And Objects Practise Questions And Solutions.html	0.1 KB
002 classesobjectssolution.zip	4.8 KB
003 Inheritance In OOPS.mp4	114.8 MB
003 Inheritance In OOPS_en.srt	32.9 KB
004 Polymorphism In OOPS.mp4	113.1 MB
004 Polymorphism In OOPS_en.srt	31.3 KB
005 Encapsulation In OOPS.mp4	134.0 MB
005 Encapsulation In OOPS_en.srt	39.9 KB
006 Abstraction In OOPS.mp4	51.9 MB
006 Abstraction In OOPS_en.srt	15.4 KB
007 Practise Assignments With Solutions.html	0.1 KB
007 inheritancesolutions.zip	4.4 KB
008 Magic Methods In Python.mp4	48.8 MB
008 Magic Methods In Python_en.srt	14.2 KB
009 Operator Overloading In Python.mp4	54.3 MB
009 Operator Overloading In Python_en.srt	15.0 KB
010 Custom Exception Handling.mp4	71.5 MB
010 Custom Exception Handling_en.srt	12.4 KB
011 Complete OOPS Practise Question With Solutions.html	0.1 KB
011 oopsquestion.zip	5.3 KB
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/12 - Advance Python/
001 Iterators In Python.mp4	20.2 MB
001 Iterators In Python_en.srt	11.4 KB
002 Generators With Practical Implementation.mp4	77.4 MB
002 Generators With Practical Implementation_en.srt	20.0 KB
003 Function Copy,Cloures And Decorators.mp4	179.4 MB
003 Function Copy,Cloures And Decorators_en.srt	39.6 KB
004 Advance Python Practise Questions And Solutions.html	0.1 KB
004 itergendecorsolutions.zip	4.6 KB
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/13 - Data Analysis With Python/
001 Numpy In Python.mp4	546.0 MB
001 Numpy In Python_en.srt	51.0 KB
002 Pandas- DataFrame And Series.mp4	580.1 MB
002 Pandas- DataFrame And Series_en.srt	52.3 KB
003 Data Manipulation With Pandas And Numpy.mp4	237.7 MB
003 Data Manipulation With Pandas And Numpy_en.srt	46.1 KB
004 Reading Data From Various Data Source Using Pandas_en.srt	27.3 KB
005 Data Visualization With Matplotlib.mp4	292.2 MB
005 Data Visualization With Matplotlib_en.srt	55.4 KB
006 Data Visualization With Seaborn.mp4	189.7 MB
006 Data Visualization With Seaborn_en.srt	34.6 KB
007 Pandas And Numpy Assignments And Solutions.html	0.2 KB
007 numpypandasassignments.zip	8.7 KB
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/14 - Working With Sqlite3/
001 Module-SQLite3-Assignments-Solution.zip	4.3 KB
001 SQLITE3 Assignments And Solutions.html	0.1 KB
002 Crud Operation With SQLite3 And Python.mp4	170.3 MB
002 Crud Operation With SQLite3 And Python_en.srt	30.2 KB
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/15 - Logging In Python/
001 Logging Practical Implementation In Python.mp4	207.0 MB
001 Logging Practical Implementation In Python_en.srt	26.8 KB
002 Logging With Multiple Loggers.mp4	47.7 MB
002 Logging With Multiple Loggers_en.srt	7.9 KB
003 Logging With A Real World Example.mp4	75.4 MB
003 Logging With A Real World Example_en.srt	13.9 KB
004 Logging Assignments And Solutions.html	0.0 KB
004 Module-Logging-Assignments-Questions.zip	4.6 KB
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/16 - Python Multi Threading and Multi Processing/
001 What Is Process And Threads.mp4	114.6 MB
001 What Is Process And Threads_en.srt	22.8 KB
002 2-Multithreading Practical Implementation With Python.mp4	39.8 MB
002 2-Multithreading Practical Implementation With Python_en.srt	20.0 KB
003 Multiprocessing Practical Implementation With Python.mp4	22.0 MB
003 Multiprocessing Practical Implementation With Python_en.srt	11.7 KB
004 Thread Pool Executor and Process Pool.mp4	24.7 MB
004 Thread Pool Executor and Process Pool_en.srt	13.2 KB
005 Implement Web Scraping Usecase With Multithreading.mp4	69.2 MB
005 Implement Web Scraping Usecase With Multithreading_en.srt	17.1 KB
006 Real World Usecase Implementation With MultiProcessing.mp4	59.0 MB
006 Real World Usecase Implementation With MultiProcessing_en.srt	11.1 KB
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/17 - Memory Management With Python/
001 Memory Allocation And DeallocationGarbage collection and Best Practises.mp4	176.3 MB
001 Memory Allocation And DeallocationGarbage collection and Best Practises_en.srt	35.7 KB
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/18 - Getting Started With Flask Framework/
001 Introduction To Flask Framework.mp4	105.3 MB
001 Introduction To Flask Framework_en.srt	19.0 KB
002 Understanding Simple Flask App Skeleton.mp4	46.3 MB
002 Understanding Simple Flask App Skeleton_en.srt	22.6 KB
003 Integrating HTML With Flask Web App.mp4	24.5 MB
003 Integrating HTML With Flask Web App_en.srt	16.2 KB
004 Working With HTTP Verbs Get And Post.mp4	117.9 MB
004 Working With HTTP Verbs Get And Post_en.srt	21.2 KB
005 Building Dynamic Url ,Variables Rule And Jinja 2 Template Engine.mp4	398.9 MB
005 Building Dynamic Url ,Variables Rule And Jinja 2 Template Engine_en.srt	63.7 KB
006 Working With Rest API's And HTTP Verbs Put And Delete.mp4	236.0 MB
006 Working With Rest API's And HTTP Verbs Put And Delete_en.srt	39.9 KB
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/19 - Getting Started With Streamlit Web Framework/
001 Building Web App Using Streamlit.mp4	100.0 MB
001 Building Web App Using Streamlit_en.srt	29.0 KB
002 Example Of ML App With Streamlit Web App.mp4	55.9 MB
002 Example Of ML App With Streamlit Web App_en.srt	13.9 KB
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/20 - Getting Started With Statistics/
001 What is Statistics And its Application.mp4	100.0 MB
001 What is Statistics And its Application_en.srt	13.9 KB
002 Types Of Statistics.mp4	22.5 MB
002 Types Of Statistics_en.srt	11.8 KB
002 Whiteboard.png	660.2 KB
003 3-PopulationVSsample-01.png	333.8 KB
003 Population Vs Sample Data.mp4	18.9 MB
003 Population Vs Sample Data_en.srt	6.6 KB
004 4-Measure-OF-Central-Tendency-01.png	718.8 KB
004 Measure Of Central Tendency.mp4	142.3 MB
004 Measure Of Central Tendency_en.srt	15.8 KB
005 5-Measure-of-Dispersion-01.png	866.0 KB
005 Measure Of Dispersion.mp4	106.6 MB
005 Measure Of Dispersion_en.srt	18.1 KB
006 Why Sample Variance Is Divided By n-1.mp4	48.4 MB
006 Why Sample Variance Is Divided By n-1_en.srt	13.2 KB
006 sample-variance.pdf	621.0 KB
007 7-Standard-Deviation-01.png	520.9 KB
007 Standard Deviation.mp4	61.8 MB
007 Standard Deviation_en.srt	9.0 KB
008 What Are Variables.mp4	81.4 MB
008 What Are Variables_en.srt	13.6 KB
008 variable.pdf	663.0 KB
009 Random-variable.pdf	1.1 MB
009 What are Random Variables.mp4	80.8 MB
009 What are Random Variables_en.srt	12.5 KB
010 10-Histograms.pdf	990.8 KB
010 Histograms- Descriptive Statistics.mp4	83.7 MB
010 Histograms- Descriptive Statistics_en.srt	14.0 KB
011 11-Percentiles-And-Quartiles.pdf	1.1 MB
011 Percentile And Quartiles- Descriptive Statistics.mp4	104.8 MB
011 Percentile And Quartiles- Descriptive Statistics_en.srt	14.5 KB
012 12-5-number-summary.pdf	734.7 KB
012 5 Number Summary-Descriptive Statistics.mp4	93.9 MB
012 5 Number Summary-Descriptive Statistics_en.srt	14.7 KB
013 8-Correlation-And-Coefficient.pdf	2.8 MB
013 Correlation And Covariance.mp4	450.7 MB
013 Correlation And Covariance_en.srt	61.9 KB
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/21 - Introduction To Probability/
001 13-Probability-Addition-rule.pdf	1.3 MB
001 Addition Rule (For Mutual And Non Mutual Exclusive Events).mp4	128.3 MB
001 Addition Rule (For Mutual And Non Mutual Exclusive Events)_en.srt	18.6 KB
002 14-Probability-Multiplication-Rule.pdf	2.1 MB
002 Probability-Multiplication Rule(Independent And Dependent Events).mp4	123.3 MB
002 Probability-Multiplication Rule(Independent And Dependent Events)_en.srt	12.5 KB
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/22 - Probability Distribution Function For Data/
001 2-finalpdf-pmf-cdf.pdf	2.4 MB
001 The Relationship Between PDF,PMF And CDF.mp4	388.0 MB
002 Types Of Probability Distribution.mp4	89.5 MB
003 3-Bernoulli-Distribution.pdf	1.9 MB
003 Bernoulli Distribution.mp4	287.3 MB
004 4-Binomial-Distribution.pdf	1.9 MB
004 Binomial Distribution.mp4	142.8 MB
004 Binomial Distribution_en.srt	24.4 KB
005 5-Poisson-Distribution.pdf	1.2 MB
005 Poisson Distribution.mp4	160.6 MB
005 Poisson Distribution_en.srt	22.6 KB
006 6-Normal-Guassian-Distribution.pdf	1.4 MB
006 Normal Gaussian Distribution.mp4	155.5 MB
006 Normal Gaussian Distribution_en.srt	22.7 KB
007 7-Standard-Normal-Distribution-And-Z-score.pdf	1.2 MB
007 Standard Normal Distribution And Z Score.mp4	247.9 MB
007 Standard Normal Distribution And Z Score_en.srt	24.2 KB
008 8-Uniform-Distribution.pdf	2.0 MB
008 Uniform Distribution.mp4	145.0 MB
008 Uniform Distribution_en.srt	22.8 KB
009 9-Log-Normal-Distribution.pdf	1.4 MB
009 Log Normal Distribution.mp4	172.4 MB
009 Log Normal Distribution_en.srt	16.4 KB
010 10-Power-Law-Distribution.pdf	1.3 MB
010 Power Law Distribution.mp4	86.6 MB
010 Power Law Distribution_en.srt	12.3 KB
011 11-Pareto-Distribution.pdf	1.3 MB
011 Pareto Distribution.mp4	33.9 MB
011 Pareto Distribution_en.srt	9.8 KB
012 12-Central-Limit-Theorem.pdf	1.4 MB
012 Central Limit Theorem.mp4	113.3 MB
012 Central Limit Theorem_en.srt	18.4 KB
013 13-Estimates.pdf	720.1 KB
013 Estimates.mp4	41.0 MB
013 Estimates_en.srt	9.4 KB
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/23 - Inferential Statistics/
001 1.0-Hypothesis-Testing-And-Mechanism.pdf	1.4 MB
001 Hypothesis Testing And Mechanism.mp4	79.2 MB
001 Hypothesis Testing And Mechanism_en.srt	11.0 KB
002 2.0-P-value.pdf	1.3 MB
002 What is P value.mp4	200.8 MB
002 What is P value_en.srt	19.6 KB
003 3-Z-test.pdf	2.8 MB
003 Z Test- Hypothesis Testing.mp4	415.4 MB
003 Z Test- Hypothesis Testing_en.srt	43.0 KB
004 4.0-sstudent-t-distribution.pdf	682.5 KB
004 Student t Distribution.mp4	58.2 MB
004 Student t Distribution_en.srt	8.0 KB
005 5.0-T-stats-t-test.pdf	1.4 MB
005 T Stats With T test Hypothesis Testing.mp4	160.7 MB
005 T Stats With T test Hypothesis Testing_en.srt	17.3 KB
006 6.0-ztestvsttest.pdf	575.7 KB
006 Z test Vs T test.mp4	17.3 MB
006 Z test Vs T test_en.srt	5.2 KB
007 7.0-type1-and-type-2-error.pdf	674.0 KB
007 Type 1 And Type 2 Error.mp4	54.3 MB
007 Type 1 And Type 2 Error_en.srt	7.7 KB
008 8.0-Bayes-theorem.pdf	1.4 MB
008 Bayes Theorem.mp4	107.6 MB
008 Bayes Theorem_en.srt	15.7 KB
009 Confidence Interval And MArgin Of Error.mp4	94.2 MB
009 Confidence Interval And MArgin Of Error_en.srt	12.6 KB
010 What is Chi Square Test.mp4	89.0 MB
010 What is Chi Square Test_en.srt	12.2 KB
011 ChiSquare Goodness OF Fit.mp4	57.2 MB
011 ChiSquare Goodness OF Fit_en.srt	18.0 KB
012 Annova Test.mp4	23.8 MB
012 Annova Test_en.srt	7.7 KB
013 Assumptions Of Annova.mp4	29.6 MB
013 Assumptions Of Annova_en.srt	7.1 KB
014 Types Of Annova.mp4	83.3 MB
014 Types Of Annova_en.srt	11.9 KB
015 Partioning Of Variance In Annova.mp4	491.8 MB
015 Partioning Of Variance In Annova_en.srt	37.6 KB
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/24 - Feature Engineering/
001 1.0-Handling-Missing-values-1.ipynb	66.6 KB
001 Handling Missing Values.mp4	311.5 MB
001 Handling Missing Values_en.srt	34.8 KB
002 2.0-Handling-Imbalance-Dataset.ipynb	11.7 KB
002 Handling Imbalanced Dataset.mp4	140.9 MB
002 Handling Imbalanced Dataset_en.srt	20.6 KB
003 3.0-SMOTE.ipynb	174.6 KB
003 Handling Imbalanced Dataset Using Smote.mp4	288.7 MB
003 Handling Imbalanced Dataset Using Smote_en.srt	22.5 KB
004 4.0-Handling-Outliers.ipynb	27.4 KB
004 Handling Outliers Using Python.mp4	88.8 MB
004 Handling Outliers Using Python_en.srt	14.1 KB
005 5.0-Nominal-or-OHE.ipynb	26.4 KB
005 Data Encoding- Nominal Or OHE.mp4	213.4 MB
005 Data Encoding- Nominal Or OHE_en.srt	21.4 KB
006 7.0-Label-and-Ordinal.ipynb	26.4 KB
006 Label And Ordinal Encoding.mp4	103.5 MB
006 Label And Ordinal Encoding_en.srt	16.0 KB
007 8.0-Target-Guided-Ordinal-Encoding.ipynb	12.6 KB
007 Target Guided Ordinal Encoding.mp4	56.8 MB
007 Target Guided Ordinal Encoding_en.srt	9.0 KB
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/25 - Exploratory Data Analysis and Feature Engineering/
001 1.0-WinequalityEDA.ipynb	429.8 KB
001 Red Wine Dataset EDA.mp4	465.1 MB
001 Red Wine Dataset EDA_en.srt	41.0 KB
002 2.0-EDA-And-FE-Flight-Price.ipynb	78.2 KB
002 EDA And Feature Engineering Flight Price Dataset.mp4	317.0 MB
002 EDA And Feature Engineering Flight Price Dataset_en.srt	53.6 KB
002 flight-price.xlsx	530.4 KB
003 3.0-EDA-And-FE-Google-Playstore.ipynb	942.4 KB
003 Data Cleaning With Google Playstore Dataset.mp4	513.5 MB
003 Data Cleaning With Google Playstore Dataset_en.srt	47.3 KB
004 Part 2- EDA Google Play Store Cleaned Dataset.mp4	291.5 MB
004 Part 2- EDA Google Play Store Cleaned Dataset_en.srt	31.2 KB
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/26 - Introduction To Machine Learning/
001 Introduction.mp4	166.4 MB
001 Introduction_en.srt	14.2 KB
002 Types of ML Techniques.mp4	304.3 MB
002 Types of ML Techniques_en.srt	25.2 KB
003 Equation of Line, 3d, and Hyperplane.mp4	221.3 MB
003 Equation of Line, 3d, and Hyperplane_en.srt	21.7 KB
004 Distance of a point from a plane.mp4	112.8 MB
004 Distance of a point from a plane_en.srt	11.5 KB
005 Instance based Vs Model based learning.mp4	256.9 MB
005 Instance based Vs Model based learning_en.srt	27.7 KB
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/27 - Understanding Complete Linear Regression Indepth Intuition And Practicals/
001 Simple Linear Regression Introduction.mp4	120.8 MB
001 Simple Linear Regression Introduction_en.srt	9.2 KB
002 Understanding Simple Linear regression Equations.mp4	131.4 MB
002 Understanding Simple Linear regression Equations_en.srt	14.3 KB
003 Cost Function.mp4	304.6 MB
003 Cost Function_en.srt	32.8 KB
004 Convergence Algorithm.mp4	199.6 MB
004 Convergence Algorithm_en.srt	19.6 KB
005 Convergence Algorithm Part02.mp4	184.8 MB
005 Convergence Algorithm Part02_en.srt	23.9 KB
006 Multiple Linear regression.mp4	39.1 MB
006 Multiple Linear regression_en.srt	10.9 KB
007 Performance Metrics.mp4	262.9 MB
007 Performance Metrics_en.srt	28.9 KB
008 MSE, MAE, RMSE.mp4	429.7 MB
008 MSE, MAE, RMSE_en.srt	37.4 KB
009 Overfitting and Underfitting.mp4	119.0 MB
009 Overfitting and Underfitting_en.srt	17.1 KB
010 Linear Regression with OLS.mp4	323.4 MB
010 Linear Regression with OLS_en.srt	33.9 KB
011 Simple Linear Regression Practical.mp4	909.9 MB
011 Simple Linear Regression Practical_en.srt	81.4 KB
012 Multiple Linear regression.mp4	615.5 MB
012 Multiple Linear regression_en.srt	52.7 KB
013 Polynomial Regression Intuition.mp4	182.0 MB
013 Polynomial Regression Intuition_en.srt	18.8 KB
014 Polynomial Regression Implementation.mp4	212.1 MB
014 Polynomial Regression Implementation_en.srt	39.4 KB
015 Pipeline in Polynomial.mp4	49.2 MB
015 Pipeline in Polynomial_en.srt	9.9 KB
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/28 - Ridge,Lasso And ElasticNet ML ALgorithms/
001 Ridge Regression.mp4	323.3 MB
001 Ridge Regression_en.srt	27.2 KB
002 Lasso & ElasticNet.mp4	176.9 MB
002 Lasso & ElasticNet_en.srt	14.9 KB
003 Types Of cross Validation.mp4	298.6 MB
003 Types Of cross Validation_en.srt	29.2 KB
004 Cleaning the Dataset.mp4	311.6 MB
004 Cleaning the Dataset_en.srt	36.6 KB
005 EDA and Feature Engineering.mp4	474.4 MB
005 EDA and Feature Engineering_en.srt	42.9 KB
006 Feature Selection.mp4	74.1 MB
006 Feature Selection_en.srt	27.5 KB
007 Model Training.mp4	81.5 MB
007 Model Training_en.srt	14.4 KB
008 Hyperparameter tuning.mp4	198.9 MB
008 Hyperparameter tuning_en.srt	19.4 KB
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/29 - Steps By Step Project Implementation With LifeCycle OF ML Project/
001 Basic Simple Linear Regression Project.mp4	419.6 MB
001 Basic Simple Linear Regression Project_en.srt	70.3 KB
002 Multiple Linear Regression Projects With Assumptions.mp4	545.2 MB
002 Multiple Linear Regression Projects With Assumptions_en.srt	46.5 KB
003 Basic Regression Project From Scratch-EDA And Feature Engineering.mp4	342.7 MB
003 Basic Regression Project From Scratch-EDA And Feature Engineering_en.srt	32.3 KB
004 Model Training With Cross Validation Using Lasso Regression.mp4	383.1 MB
004 Model Training With Cross Validation Using Lasso Regression_en.srt	45.4 KB
005 Model Training With Ridge and Elastic net With Cross Validation.mp4	54.2 MB
005 Model Training With Ridge and Elastic net With Cross Validation_en.srt	10.2 KB
006 Model Pickling In ML Project.mp4	16.3 MB
006 Model Pickling In ML Project_en.srt	5.9 KB
007 End To End ML Project Implementation.mp4	651.8 MB
007 End To End ML Project Implementation_en.srt	55.6 KB
008 Project Deployment In AWS.mp4	73.9 MB
008 Project Deployment In AWS_en.srt	21.5 KB
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/30 - Logistic Regression/
001 Can Linear Regression Solve Classifier Problem.mp4	128.3 MB
001 Can Linear Regression Solve Classifier Problem_en.srt	21.7 KB
002 Logistic Regression Indepth Math Intuition.mp4	373.7 MB
002 Logistic Regression Indepth Math Intuition_en.srt	31.3 KB
003 Performance Metrics.mp4	372.4 MB
003 Performance Metrics_en.srt	39.9 KB
004 Logistic Regression OVR.mp4	161.0 MB
004 Logistic Regression OVR_en.srt	15.1 KB
005 Logistic Regression Implementation.mp4	257.5 MB
005 Logistic Regression Implementation_en.srt	23.7 KB
006 Grid Search Hyper Parameter.mp4	180.9 MB
006 Grid Search Hyper Parameter_en.srt	21.3 KB
007 Randomised Search CV.mp4	69.1 MB
007 Randomised Search CV_en.srt	8.0 KB
008 Logistic OVR.mp4	61.5 MB
008 Logistic OVR_en.srt	7.5 KB
009 Logistic Imbalanced Dataset.mp4	183.8 MB
009 Logistic Imbalanced Dataset_en.srt	17.4 KB
010 Logistic Regression ROC.mp4	187.2 MB
010 Logistic Regression ROC_en.srt	32.7 KB
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/31 - Support Vector Machines/
001 Introduction to support vector Machine.mp4	54.4 MB
001 Introduction to support vector Machine_en.srt	13.9 KB
002 SoftMargin and Hard Margin.mp4	28.1 MB
002 SoftMargin and Hard Margin_en.srt	3.8 KB
003 SVM Maths Intuition.mp4	131.3 MB
003 SVM Maths Intuition_en.srt	18.3 KB
004 SVC Cost function.mp4	141.6 MB
004 SVC Cost function_en.srt	10.3 KB
005 Support Vector Regression.mp4	164.7 MB
005 Support Vector Regression_en.srt	17.6 KB
006 SVM Kernels.mp4	125.4 MB
006 SVM Kernels_en.srt	17.6 KB
007 Support Vector Classifiers.mp4	266.7 MB
007 Support Vector Classifiers_en.srt	29.3 KB
008 SVM Kernels implementation.mp4	262.3 MB
008 SVM Kernels implementation_en.srt	24.2 KB
009 Support Vector Regression Implementation.mp4	208.1 MB
009 Support Vector Regression Implementation_en.srt	32.6 KB
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/32 - Naive Bayes Theorem/
001 Understanding Baye's Theorem.mp4	547.2 MB
001 Understanding Baye's Theorem_en.srt	59.9 KB
002 Variants Of Naive Baye's.mp4	127.4 MB
002 Variants Of Naive Baye's_en.srt	18.8 KB
003 Naive Baye's Practical Implementation.mp4	102.8 MB
003 Naive Baye's Practical Implementation_en.srt	17.9 KB
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/33 - K Nearest Neighbour ML Algorithm/
001 KNN Classification And Regression Indepth Intuition.mp4	251.3 MB
001 KNN Classification And Regression Indepth Intuition_en.srt	24.7 KB
002 Optimization Of KNN- KDtree And Ball Tree Indepth Intuition.mp4	241.1 MB
002 Optimization Of KNN- KDtree And Ball Tree Indepth Intuition_en.srt	27.1 KB
003 KNN Classifier And Regressor Classification.mp4	65.7 MB
003 KNN Classifier And Regressor Classification_en.srt	12.1 KB
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/34 - Decision Tree Classifier And Regressor/
001 Introduction TO Decision Tree.mp4	131.9 MB
001 Introduction TO Decision Tree_en.srt	22.8 KB
002 Entropy and Gini Impurity.mp4	174.3 MB
002 Entropy and Gini Impurity_en.srt	20.7 KB
003 Information Gain.mp4	184.8 MB
003 Information Gain_en.srt	15.5 KB
004 Entropy vs Gini impurity.mp4	43.3 MB
004 Entropy vs Gini impurity_en.srt	5.1 KB
005 Decision Tree Split for Numerical Features.mp4	52.9 MB
005 Decision Tree Split for Numerical Features_en.srt	8.9 KB
006 Post Pruning & Pre Pruning.mp4	89.3 MB
006 Post Pruning & Pre Pruning_en.srt	15.1 KB
007 Decision Tree Regression.mp4	428.6 MB
007 Decision Tree Regression_en.srt	34.1 KB
008 Decision Tree Implementation.mp4	326.0 MB
008 Decision Tree Implementation_en.srt	27.0 KB
009 Decision tree Prepruning.mp4	83.8 MB
009 Decision tree Prepruning_en.srt	14.0 KB
010 Diabetes Prediction Using Decision Tree Regressor.mp4	193.2 MB
010 Diabetes Prediction Using Decision Tree Regressor_en.srt	18.4 KB
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/35 - Random Forest Machine Learning/
001 Bagging & Boosting Ensemble Techniques.mp4	159.0 MB
001 Bagging & Boosting Ensemble Techniques_en.srt	23.7 KB
002 Random Forest Regression.mp4	132.9 MB
002 Random Forest Regression_en.srt	19.9 KB
003 Problem Classification.mp4	31.3 MB
003 Problem Classification_en.srt	5.5 KB
004 Feature Engineering Part 01.mp4	128.0 MB
004 Feature Engineering Part 01_en.srt	24.4 KB
005 Feature Engineering Part 02.mp4	84.5 MB
005 Feature Engineering Part 02_en.srt	16.2 KB
006 Model Training Step.mp4	115.4 MB
006 Model Training Step_en.srt	21.1 KB
007 Random Forest Regression Project-Problem Statement.mp4	19.7 MB
007 Random Forest Regression Project-Problem Statement_en.srt	3.8 KB
008 Feature Engineering.mp4	168.9 MB
008 Feature Engineering_en.srt	20.6 KB
009 Model Training.mp4	69.8 MB
009 Model Training_en.srt	12.4 KB
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/36 - Adaboost Machine Learning Algorithm/
001 Introduction to Adaboost ML algorithm.mp4	130.5 MB
001 Introduction to Adaboost ML algorithm_en.srt	17.8 KB
002 Creating Decision Tree Stump.mp4	81.7 MB
002 Creating Decision Tree Stump_en.srt	13.6 KB
003 Performance of Decision Tree Stump.mp4	160.5 MB
003 Performance of Decision Tree Stump_en.srt	12.7 KB
004 Updating Weights.mp4	55.3 MB
004 Updating Weights_en.srt	8.6 KB
005 Normalising Weights and Assigning Bins.mp4	92.6 MB
005 Normalising Weights and Assigning Bins_en.srt	9.7 KB
006 Selecting New Datapoints for Next tree.mp4	122.8 MB
006 Selecting New Datapoints for Next tree_en.srt	10.6 KB
007 Final Prediction for Adaboost.mp4	93.5 MB
007 Final Prediction for Adaboost_en.srt	7.7 KB
008 Adaboost Model Training.mp4	215.4 MB
008 Adaboost Model Training_en.srt	21.0 KB
009 Adaboost Regressor Model Training.mp4	114.7 MB
009 Adaboost Regressor Model Training_en.srt	13.9 KB
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/37 - Gradient Boosting/
001 Gradient Boosting Regression.mp4	235.3 MB
001 Gradient Boosting Regression_en.srt	24.4 KB
002 Gradient Boost Classifier Training.mp4	126.2 MB
002 Gradient Boost Classifier Training_en.srt	14.9 KB
003 Gradient Boost Regression Model Training.mp4	148.3 MB
003 Gradient Boost Regression Model Training_en.srt	17.5 KB
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/38 - Xgboost Machine Learning Algorithms/
001 Xgboost Classification Indepth Intuit.mp4	580.5 MB
001 Xgboost Classification Indepth Intuit_en.srt	48.8 KB
002 Xgboost Regressor.mp4	340.0 MB
002 Xgboost Regressor_en.srt	34.5 KB
003 Model Training Xgboost.mp4	160.1 MB
003 Model Training Xgboost_en.srt	14.1 KB
004 Xgboost Regressor Training.mp4	104.8 MB
004 Xgboost Regressor Training_en.srt	8.9 KB
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/39 - Unsupervised Machine Learning/
001 Introduction To Unsupervised Machine Learning.mp4	84.6 MB
001 Introduction To Unsupervised Machine Learning_en.srt	11.5 KB
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/40 - PCA/
001 Curse Of Dimensionality.mp4	153.1 MB
001 Curse Of Dimensionality_en.srt	24.0 KB
002 Feature Selection and Extraction.mp4	283.6 MB
002 Feature Selection and Extraction_en.srt	28.4 KB
003 PCA Geometric Intuition.mp4	172.3 MB
003 PCA Geometric Intuition_en.srt	24.7 KB
004 PCA Maths Intuition 01.mp4	180.1 MB
004 PCA Maths Intuition 01_en.srt	18.2 KB
005 Eigen Decomposition on Covariance Matrix.mp4	343.3 MB
005 Eigen Decomposition on Covariance Matrix_en.srt	26.2 KB
006 PCA Implementation.mp4	67.5 MB
006 PCA Implementation_en.srt	20.4 KB
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/41 - K Means Clustering Unsupervised ML/
001 Kmeans Clustering Geometric Intuition.mp4	129.9 MB
001 Kmeans Clustering Geometric Intuition_en.srt	21.5 KB
002 How to Find K Values.mp4	112.3 MB
002 How to Find K Values_en.srt	18.0 KB
003 Random Initialisation Trap(Kmeans++).mp4	98.6 MB
003 Random Initialisation Trap(Kmeans++)_en.srt	9.7 KB
004 K means Clustering Implementation.mp4	403.2 MB
004 K means Clustering Implementation_en.srt	35.3 KB
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/42 - Hierarichal Clustering/
001 Hierarichal Clustering.mp4	300.8 MB
001 Hierarichal Clustering_en.srt	26.3 KB
002 Agglomerative Clustering Implementation.mp4	207.5 MB
002 Agglomerative Clustering Implementation_en.srt	22.5 KB
003 Kmeans vs Hierarical Mean Clustering.mp4	56.3 MB
003 Kmeans vs Hierarical Mean Clustering_en.srt	6.4 KB
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/43 - DBSCAN Clustering/
001 How DBSCAN Works.mp4	136.0 MB
001 How DBSCAN Works_en.srt	15.7 KB
002 Examples After Applying DBSCAN.mp4	51.8 MB
002 Examples After Applying DBSCAN_en.srt	5.2 KB
003 Pros and Cons Of DBSCAN.mp4	126.9 MB
003 Pros and Cons Of DBSCAN_en.srt	13.5 KB
004 DBSCAN Clustering Implementation.mp4	66.5 MB
004 DBSCAN Clustering Implementation_en.srt	10.0 KB
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/44 - Silhoutte Clustering/
001 Silhoutte Clustering Intuition.mp4	91.4 MB
001 Silhoutte Clustering Intuition_en.srt	16.1 KB
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/45 - Anomaly Detection Machine Learning Algorithms/
001 Anomaly Detection USsing Isolation Forest Indepth Intuition.mp4	469.0 MB
001 Anomaly Detection USsing Isolation Forest Indepth Intuition_en.srt	38.6 KB
002 DBSCAN Clustering Anomaly Detection.mp4	130.3 MB
002 DBSCAN Clustering Anomaly Detection_en.srt	13.7 KB
003 Local Outlier Factor Anomaly Detection.mp4	79.4 MB
003 Local Outlier Factor Anomaly Detection_en.srt	13.0 KB
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/46 - Dockers For Beginners/
001 Dockers Series.mp4	4.7 MB
001 Dockers Series_en.srt	1.6 KB
002 Dockers and What is Containers.mp4	208.4 MB
002 Dockers and What is Containers_en.srt	20.4 KB
003 Docker image vs Containers.mp4	65.5 MB
003 Docker image vs Containers_en.srt	9.1 KB
004 Docker vs Virtual Machines.mp4	132.6 MB
004 Docker vs Virtual Machines_en.srt	11.7 KB
005 Docker Installation.mp4	122.5 MB
005 Docker Installation_en.srt	21.1 KB
006 Docker Basic Commands.mp4	195.9 MB
006 Docker Basic Commands_en.srt	33.6 KB
007 Creating a Docker Image.mp4	75.2 MB
007 Creating a Docker Image_en.srt	24.4 KB
008 Push Docker Image to Docker Hub.mp4	82.3 MB
008 Push Docker Image to Docker Hub_en.srt	14.8 KB
009 9-Dockers-Compose.mp4	828.8 MB
009 Docker Compose.mp4	275.9 MB
009 Docker Compose_en.srt	34.0 KB
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/47 - GIT For Beginners/
001 Introduction, Installation and Basic Commands.mp4	196.2 MB
001 Introduction, Installation and Basic Commands_en.srt	37.3 KB
002 Git Merge, Push, Checkout and Log with commands.mp4	224.9 MB
002 Git Merge, Push, Checkout and Log with commands_en.srt	24.4 KB
003 Resolving Git Branch Merge Conflict.mp4	344.2 MB
003 Resolving Git Branch Merge Conflict_en.srt	30.1 KB
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/48 - End To End Machine Learning Project With AWS,Azure Deployment/
001 End To End ML Project With Deployment-Github And Code Set Up.mp4	704.0 MB
001 End To End ML Project With Deployment-Github And Code Set Up_en.srt	64.8 KB
002 Implementing Project Structure, Logging And Exception Handling.mp4	659.4 MB
002 Implementing Project Structure, Logging And Exception Handling_en.srt	60.4 KB
003 Discussing Project Problem Statement,EDA And Model Training.mp4	676.4 MB
003 Discussing Project Problem Statement,EDA And Model Training_en.srt	70.9 KB
004 Data Ingestion Implementation.mp4	268.1 MB
004 Data Ingestion Implementation_en.srt	46.1 KB
005 Data Transformation Using Pipelines Implementation.mp4	369.0 MB
005 Data Transformation Using Pipelines Implementation_en.srt	63.5 KB
006 Model Trainer Implementation.mp4	251.5 MB
006 Model Trainer Implementation_en.srt	40.4 KB
007 Model Hyperparameter Tuning Implementation.mp4	69.7 MB
007 Model Hyperparameter Tuning Implementation_en.srt	12.7 KB
008 Building Prediction Pipeline.mp4	264.3 MB
008 Building Prediction Pipeline_en.srt	46.3 KB
009 ML Project Deployment Using AWS Beanstalk.mp4	171.5 MB
009 ML Project Deployment Using AWS Beanstalk_en.srt	32.7 KB
010 Deployment EC2 Instance With ECR.mp4	446.0 MB
010 Deployment EC2 Instance With ECR_en.srt	74.0 KB
011 Deployment Azure With Container And Images.mp4	462.8 MB
011 Deployment Azure With Container And Images_en.srt	42.6 KB
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/49 - End To End MLOPS Projects With ETL Pipelines- Building Network Security System/
001 Project Structure Set up With Environment.mp4	65.3 MB
001 Project Structure Set up With Environment_en.srt	31.3 KB
001 finalnetworksecurity.pdf	3.6 MB
001 networksecurity.zip	3.6 MB
002 Github Repository Set Up With VS Code.mp4	114.7 MB
002 Github Repository Set Up With VS Code_en.srt	22.3 KB
003 Packaging the Project With Setup.py.mp4	264.6 MB
003 Packaging the Project With Setup.py_en.srt	29.9 KB
004 Logging And Exception Handling Implementation.mp4	236.8 MB
004 Logging And Exception Handling Implementation_en.srt	25.9 KB
005 Introduction To ETL Pipelines.mp4	65.6 MB
005 Introduction To ETL Pipelines_en.srt	13.5 KB
006 Setting Up MongoDb Atlas.mp4	187.7 MB
006 Setting Up MongoDb Atlas_en.srt	20.7 KB
007 ETL Pipeline Setup With Python.mp4	337.9 MB
007 ETL Pipeline Setup With Python_en.srt	38.0 KB
008 Data Ingestion Architecture.mp4	52.8 MB
008 Data Ingestion Architecture_en.srt	9.9 KB
009 Implementing Data Ingestion Configuration.mp4	233.4 MB
009 Implementing Data Ingestion Configuration_en.srt	34.3 KB
010 Implementing Data Ingestions Component.mp4	587.2 MB
010 Implementing Data Ingestions Component_en.srt	60.8 KB
011 Implementing Data Validation-Part 1.mp4	432.4 MB
011 Implementing Data Validation-Part 1_en.srt	48.6 KB
012 Implementing Data Validation-Part 2.mp4	493.7 MB
012 Implementing Data Validation-Part 2_en.srt	58.0 KB
013 Data Transformation Architecture.mp4	245.0 MB
013 Data Transformation Architecture_en.srt	32.0 KB
014 Data Transformation Implementation.mp4	557.1 MB
014 Data Transformation Implementation_en.srt	50.8 KB
015 Model Trainer Implementation- Part 1.mp4	402.5 MB
015 Model Trainer Implementation- Part 1_en.srt	42.7 KB
016 Model Trainer And Evaluation With Hyperparameter Tuning.mp4	369.7 MB
016 Model Trainer And Evaluation With Hyperparameter Tuning_en.srt	36.0 KB
017 Model Experiment Tracking With MLFLOW.mp4	155.2 MB
017 Model Experiment Tracking With MLFLOW_en.srt	29.3 KB
018 MLFLOW Experiment Tracking With Remote Respository Dagshub.mp4	89.6 MB
018 MLFLOW Experiment Tracking With Remote Respository Dagshub_en.srt	18.3 KB
019 Model Pusher Implementation.mp4	41.9 MB
019 Model Pusher Implementation_en.srt	7.9 KB
020 Model Training Pipeline Implementation.mp4	467.8 MB
020 Model Training Pipeline Implementation_en.srt	46.1 KB
021 Batch Prediction Pipeline Implementation.mp4	201.3 MB
021 Batch Prediction Pipeline Implementation_en.srt	21.3 KB
022 Final Model And Artifacts Pusher To AWS S3 buckets.mp4	347.0 MB
022 Final Model And Artifacts Pusher To AWS S3 buckets_en.srt	35.6 KB
023 Building Docker Image And Github Actions.mp4	44.2 MB
023 Building Docker Image And Github Actions_en.srt	18.1 KB
024 Github Action-Docker Image Push to AWS ECR Repo Implementation.mp4	294.9 MB
024 Github Action-Docker Image Push to AWS ECR Repo Implementation_en.srt	31.6 KB
025 Final Deployment To EC2 instance.mp4	365.2 MB
025 Final Deployment To EC2 instance_en.srt	41.0 KB
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/50 - MLFlow Dagshub and BentoML-Complete ML Project Lifecycle/
001 Getting Started With MLOPS With MLFlow And Dagshub With Project.mp4	652.7 MB
001 Getting Started With MLOPS With MLFlow And Dagshub With Project_en.srt	77.3 KB
002 Data Versioning Control Implementation.mp4	265.8 MB
002 Data Versioning Control Implementation_en.srt	44.2 KB
003 Building Data Science Projects With BentoML.mp4	304.0 MB
003 Building Data Science Projects With BentoML_en.srt	50.4 KB
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/51 - NLP for Machine Learning/
001 Roadmap to Learn NLP for Machine Learning.mp4	261.0 MB
001 Roadmap to Learn NLP for Machine Learning_en.srt	25.3 KB
002 Practical Use cases of NLP.mp4	101.6 MB
002 Practical Use cases of NLP_en.srt	10.3 KB
003 Tokenisation and Basic Terminologies.mp4	108.1 MB
003 Tokenisation and Basic Terminologies_en.srt	14.6 KB
004 Tokenisation Practicals.mp4	251.1 MB
004 Tokenisation Practicals_en.srt	24.9 KB
005 Text Preprocessing Stemming using NLTK.mp4	256.5 MB
005 Text Preprocessing Stemming using NLTK_en.srt	34.9 KB
006 Text Preprocessing Lemmatization NLTK.mp4	86.4 MB
006 Text Preprocessing Lemmatization NLTK_en.srt	18.2 KB
007 Text Preprocessing Stopwords.mp4	343.6 MB
007 Text Preprocessing Stopwords_en.srt	36.8 KB
008 Parts of Speech Tagging Using NLTK.mp4	203.7 MB
008 Parts of Speech Tagging Using NLTK_en.srt	20.7 KB
009 Named Entity Recognition.mp4	57.7 MB
009 Named Entity Recognition_en.srt	11.5 KB
010 What's Next.mp4	116.1 MB
010 What's Next_en.srt	20.2 KB
011 One Hot Encoding Intuition.mp4	85.9 MB
011 One Hot Encoding Intuition_en.srt	13.6 KB
012 Advantages and Disadvantages of OHE.mp4	176.2 MB
012 Advantages and Disadvantages of OHE_en.srt	20.3 KB
013 Bag of Words Intuition.mp4	199.3 MB
013 Bag of Words Intuition_en.srt	17.8 KB
014 Advantages and Disadvantages BOW.mp4	144.9 MB
014 Advantages and Disadvantages BOW_en.srt	17.7 KB
015 BOW implementation using NLTK.mp4	295.2 MB
015 BOW implementation using NLTK_en.srt	36.2 KB
016 N Grams.mp4	40.8 MB
016 N Grams_en.srt	13.1 KB
017 N Gram BOW Implementation Using NLTK.mp4	123.6 MB
017 N Gram BOW Implementation Using NLTK_en.srt	13.4 KB
018 TF-IDF Instituion.mp4	155.9 MB
018 TF-IDF Instituion_en.srt	17.8 KB
019 Advantages and Disadvantages of TF-IDF.mp4	53.3 MB
019 Advantages and Disadvantages of TF-IDF_en.srt	9.3 KB
020 TFIDF Practical implementation Python.mp4	63.3 MB
020 TFIDF Practical implementation Python_en.srt	12.3 KB
021 Word Embeddings.mp4	71.2 MB
021 Word Embeddings_en.srt	11.3 KB
022 Word2Vec Intuition.mp4	276.3 MB
022 Word2Vec Intuition_en.srt	32.1 KB
023 Word2Vec Cbow Intuition.mp4	93.6 MB
023 Word2Vec Cbow Intuition_en.srt	34.6 KB
024 SkipGram Indepth Intuition.mp4	194.1 MB
024 SkipGram Indepth Intuition_en.srt	15.4 KB
025 Advantages of Word2Vec.mp4	21.2 MB
025 Advantages of Word2Vec_en.srt	7.7 KB
026 AvgWord2vec Indepth Intuition.mp4	70.6 MB
026 AvgWord2vec Indepth Intuition_en.srt	10.9 KB
027 Word2vec Practical Implementation Gensim.mp4	99.5 MB
027 Word2vec Practical Implementation Gensim_en.srt	13.4 KB
028 Spam ham Project using BOW.mp4	116.0 MB
028 Spam ham Project using BOW_en.srt	20.6 KB
029 Spam And Ham Project Using TFidf.mp4	51.9 MB
029 Spam And Ham Project Using TFidf_en.srt	8.2 KB
030 Best Practises For Solving ML Problems.mp4	162.4 MB
030 Best Practises For Solving ML Problems_en.srt	18.1 KB
031 Part 1-Text Classification With Word2vec And AvgWord2vec.mp4	291.6 MB
031 Part 1-Text Classification With Word2vec And AvgWord2vec_en.srt	33.1 KB
032 Part 2- Text Classification With Word2vec And AvgWord2vec.mp4	238.6 MB
032 Part 2- Text Classification With Word2vec And AvgWord2vec_en.srt	25.7 KB
033 Part 1-Kindle Review Sentiment Analysis.mp4	464.2 MB
033 Part 1-Kindle Review Sentiment Analysis_en.srt	38.7 KB
034 Part 2- Kindle Review Sentiment Analysis.mp4	83.1 MB
034 Part 2- Kindle Review Sentiment Analysis_en.srt	13.2 KB
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/52 - Deep Learning/
001 Introduction.mp4	83.2 MB
001 Introduction_en.srt	12.8 KB
002 Why Deep Learning is getting Popular.mp4	192.1 MB
002 Why Deep Learning is getting Popular_en.srt	20.8 KB
003 3 - Perception Intuition.mp4	188.3 MB
003 3 - Perception Intuition_en.srt	29.9 KB
004 Advantages and Disadvantages of Perceptron.mp4	69.2 MB
004 Advantages and Disadvantages of Perceptron_en.srt	12.3 KB
005 ANN Intuition and Learning.mp4	405.4 MB
005 ANN Intuition and Learning_en.srt	35.3 KB
006 Back Propogation and Weight Updation.mp4	384.7 MB
006 Back Propogation and Weight Updation_en.srt	33.0 KB
007 Chain Rule of Derivatives.mp4	167.8 MB
007 Chain Rule of Derivatives_en.srt	19.1 KB
008 Vanishing Gradient Problem and Sigmoid.mp4	330.3 MB
008 Vanishing Gradient Problem and Sigmoid_en.srt	36.4 KB
009 Sigmoid Activation Function.mp4	97.0 MB
009 Sigmoid Activation Function_en.srt	15.4 KB
010 Sigmoid Activation Function 2.0.mp4	196.2 MB
010 Sigmoid Activation Function 2.0_en.srt	25.0 KB
011 Tanh Activation Function.mp4	55.8 MB
011 Tanh Activation Function_en.srt	12.5 KB
012 Relu activation Function.mp4	154.0 MB
012 Relu activation Function_en.srt	17.2 KB
013 Leaky Relu and Parametric Relu.mp4	66.1 MB
013 Leaky Relu and Parametric Relu_en.srt	7.7 KB
014 ELU Activation Function.mp4	39.5 MB
014 ELU Activation Function_en.srt	6.9 KB
015 Softmax For Multiclass Classification.mp4	113.3 MB
015 Softmax For Multiclass Classification_en.srt	19.4 KB
016 Which Activation Function To Apply When.mp4	24.9 MB
016 Which Activation Function To Apply When_en.srt	9.6 KB
017 Loss Function Vs Cost Function.mp4	67.8 MB
017 Loss Function Vs Cost Function_en.srt	11.9 KB
018 Regression Cost Function.mp4	239.9 MB
018 Regression Cost Function_en.srt	28.1 KB
019 Loss Function Classification Problem.mp4	301.3 MB
019 Loss Function Classification Problem_en.srt	33.7 KB
020 Which Loss Function To Use When.mp4	17.0 MB
020 Which Loss Function To Use When_en.srt	6.6 KB
021 Gradient Descent Optimisers.mp4	174.6 MB
021 Gradient Descent Optimisers_en.srt	20.4 KB
022 SGD.mp4	137.5 MB
022 SGD_en.srt	13.9 KB
023 Mini Batch With SGD.mp4	150.5 MB
023 Mini Batch With SGD_en.srt	17.0 KB
024 SGD With Momentum.mp4	187.5 MB
024 SGD With Momentum_en.srt	21.0 KB
025 Adagard.mp4	84.3 MB
025 Adagard_en.srt	13.3 KB
026 RMSPROP.mp4	35.6 MB
026 RMSPROP_en.srt	11.2 KB
027 Adam Optimiser.mp4	94.7 MB
027 Adam Optimiser_en.srt	11.0 KB
028 Exploding Gradient Problem.mp4	142.1 MB
028 Exploding Gradient Problem_en.srt	18.4 KB
029 Weight Initialisation Techniques.mp4	117.9 MB
029 Weight Initialisation Techniques_en.srt	19.8 KB
030 Dropout Layers.mp4	178.1 MB
030 Dropout Layers_en.srt	22.6 KB
031 CNN Introduction.mp4	121.8 MB
031 CNN Introduction_en.srt	14.4 KB
032 Human Brain Vs CNN.mp4	109.3 MB
032 Human Brain Vs CNN_en.srt	12.9 KB
033 All you need to Know about Images.mp4	100.4 MB
033 All you need to Know about Images_en.srt	11.4 KB
034 Convolution Operation In CNN.mp4	154.2 MB
034 Convolution Operation In CNN_en.srt	28.2 KB
035 Padding In CNN.mp4	32.8 MB
035 Padding In CNN_en.srt	10.2 KB
036 Operation Of CNN Vs ANN.mp4	74.7 MB
036 Operation Of CNN Vs ANN_en.srt	14.5 KB
037 Max, Min and Average Pooling.mp4	101.5 MB
037 Max, Min and Average Pooling_en.srt	18.6 KB
038 Flattening and Fully Connected Layers.mp4	144.8 MB
038 Flattening and Fully Connected Layers_en.srt	14.3 KB
039 CNN example with RGB.mp4	42.8 MB
039 CNN example with RGB_en.srt	7.8 KB
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/53 - End to End Deep Learning Project Using ANN/
001 Discussing Classification Problem Statement And Setting Up Vs Code.mp4	148.5 MB
001 Discussing Classification Problem Statement And Setting Up Vs Code_en.srt	21.1 KB
001 annclassification.zip	327.2 KB
002 Feature Transformation Using Sklearn With ANN.mp4	219.0 MB
002 Feature Transformation Using Sklearn With ANN_en.srt	38.0 KB
003 Step By Step Training With ANN With Optimizer and Loss Functions.mp4	381.1 MB
003 Step By Step Training With ANN With Optimizer and Loss Functions_en.srt	65.1 KB
004 Prediction With Trained ANN Model.mp4	140.2 MB
004 Prediction With Trained ANN Model_en.srt	24.8 KB
005 Integrating ANN Model With Streamlit Web APP.mp4	81.0 MB
005 Integrating ANN Model With Streamlit Web APP_en.srt	14.4 KB
006 Deploying Streamlit web app with ANN Model.mp4	28.3 MB
006 Deploying Streamlit web app with ANN Model_en.srt	8.5 KB
007 ANN Regresiion Practical Implementation.mp4	172.7 MB
007 ANN Regresiion Practical Implementation_en.srt	29.3 KB
008 Finding Optimal Hidden Layers And Hidden Neurons In ANN.mp4	163.3 MB
008 Finding Optimal Hidden Layers And Hidden Neurons In ANN_en.srt	28.1 KB
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/54 - NLP With Deep Learning/
001 Introduction To NLP In Deep Learning.mp4	363.2 MB
001 Introduction To NLP In Deep Learning_en.srt	26.0 KB
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/55 - Simple RNN Indepth Intuition/
001 5-Problems-With-RNN.zip	6.5 MB
001 Understanding RNN Architecture- RNN Vs ANN.mp4	210.0 MB
001 Understanding RNN Architecture- RNN Vs ANN_en.srt	35.9 KB
002 Forward Propogation With Time In RNN Training.mp4	198.6 MB
002 Forward Propogation With Time In RNN Training_en.srt	33.2 KB
003 Backward Propogation With Time In RNN Training.mp4	396.1 MB
003 Backward Propogation With Time In RNN Training_en.srt	49.3 KB
004 Problems With RNN.mp4	350.7 MB
004 Problems With RNN_en.srt	44.0 KB
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/56 - End To End Deep Learning Project With Simple RNN/
001 Problem Statement.mp4	72.3 MB
001 Problem Statement_en.srt	11.2 KB
001 simple-rnn-imdb.zip	14.9 MB
002 Getting Started With Word Embedding Layers.mp4	121.6 MB
002 Getting Started With Word Embedding Layers_en.srt	23.9 KB
003 Implementing Word Embedding With Keras Tensorflow.mp4	119.8 MB
003 Implementing Word Embedding With Keras Tensorflow_en.srt	30.5 KB
004 Loading And Understanding IMDB Dataset And Feature Engineering.mp4	86.8 MB
004 Loading And Understanding IMDB Dataset And Feature Engineering_en.srt	23.8 KB
005 Training Simple RNN With Embedding Layer.mp4	47.7 MB
005 Training Simple RNN With Embedding Layer_en.srt	11.5 KB
006 Prediction From Trained Simple RNN.mp4	50.2 MB
006 Prediction From Trained Simple RNN_en.srt	12.9 KB
007 End To End Streamlit Web App Integrated With RNN And deployment.mp4	87.4 MB
007 End To End Streamlit Web App Integrated With RNN And deployment_en.srt	14.8 KB
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/57 - LSTM And GRU RNN Indepth Intuition/
001 Complete-LSTM-And-GRU.pdf	8.1 MB
001 Why LSTM RNN.mp4	199.5 MB
001 Why LSTM RNN_en.srt	31.9 KB
002 LSTM RNN Architecture.mp4	49.6 MB
002 LSTM RNN Architecture_en.srt	19.2 KB
003 Forget Gate In LSTM RNN.mp4	179.3 MB
003 Forget Gate In LSTM RNN_en.srt	24.6 KB
004 Input Gate And Candidate Memory In LSTM RNN.mp4	120.0 MB
004 Input Gate And Candidate Memory In LSTM RNN_en.srt	19.0 KB
005 Output Gate In LSTM RNN.mp4	110.7 MB
005 Output Gate In LSTM RNN_en.srt	13.9 KB
006 Training Process In LSTM RNN.mp4	177.2 MB
006 Training Process In LSTM RNN_en.srt	26.5 KB
007 Variants Of LSTM RNN.mp4	108.0 MB
007 Variants Of LSTM RNN_en.srt	19.8 KB
008 GRU RNN Complete Indepth Intuition.mp4	370.0 MB
008 GRU RNN Complete Indepth Intuition_en.srt	41.9 KB
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/58 - LSTM And GRU End To End Deep Learning Project- Predicting Next Word/
001 Discussing Problem Statement.mp4	36.5 MB
001 Discussing Problem Statement_en.srt	8.3 KB
001 LSTM-RNN.zip	26.7 MB
002 Data Collection And Data Processing.mp4	147.3 MB
002 Data Collection And Data Processing_en.srt	27.2 KB
003 LSTM Neural Network Model Training.mp4	59.5 MB
003 LSTM Neural Network Model Training_en.srt	15.5 KB
004 Prediction From LSTM Model.mp4	49.4 MB
004 Prediction From LSTM Model_en.srt	11.8 KB
005 Streamlit Webapp Integration With LSTM Trained Model.mp4	56.0 MB
005 Streamlit Webapp Integration With LSTM Trained Model_en.srt	9.7 KB
006 GRU RNN Variant Practical Implementation.mp4	15.9 MB
006 GRU RNN Variant Practical Implementation_en.srt	3.6 KB
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/59 - Bidirectional RNN Architecture And Indepth Intuition/
001 Bidirection-RNN.pdf	1.5 MB
001 Bidirectional RNN Architecture and Intuition.mp4	232.4 MB
001 Bidirectional RNN Architecture and Intuition_en.srt	35.9 KB
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/60 - Encoder Decoder Sequence To Sequence Architecture/
001 EncoderDecoderSeq2SEq.pdf	2.9 MB
001 Indepth Intuition Of Encoder And Decoder-Sequence to Sequence Architecture.mp4	416.3 MB
001 Indepth Intuition Of Encoder And Decoder-Sequence to Sequence Architecture_en.srt	49.5 KB
002 Problems With Encoder And Decoder.mp4	126.0 MB
002 Problems With Encoder And Decoder_en.srt	16.4 KB
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/61 - Attention Mechanism- Seq2Seq Networks/
001 Attention Mechanism Indepth Architecture Explanation.mp4	374.4 MB
001 Attention Mechanism Indepth Architecture Explanation_en.srt	49.5 KB
001 Attention-Mechanism.pdf	4.0 MB
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/62 - Transformers/
001 Plan Of Action.mp4	38.4 MB
001 Plan Of Action_en.srt	7.5 KB
001 Transformer-illustration.url	0.1 KB
001 best-final-transformers.pdf	26.6 MB
002 What And Why To Use Transformers.mp4	203.2 MB
003 Understanding the basic architecture of transformers.mp4	204.5 MB
004 Self Attention Layer Working.mp4	774.0 MB
005 Multi Head Attention.mp4	131.9 MB
006 Feed Forward Neural Network With Multi Head Attention.mp4	113.9 MB
007 Positional Encoding Indepth Intuition.mp4	368.4 MB
007 Positional Encoding Indepth Intuition_en.srt	44.4 KB
008 Layer Normalization.mp4	429.7 MB
008 Layer Normalization_en.srt	52.7 KB
009 Layer Normalization Examples.mp4	32.6 MB
009 Layer Normalization Examples_en.srt	10.5 KB
010 Complete Encoder transformer architecture.mp4	267.6 MB
010 Complete Encoder transformer architecture_en.srt	35.9 KB
011 Decoder Transformer- Plan Of Action.mp4	87.3 MB
011 Decoder Transformer- Plan Of Action_en.srt	11.6 KB
012 Decoder Transformer- Masked Multi Head Attention Working.mp4	608.2 MB
012 Decoder Transformer- Masked Multi Head Attention Working_en.srt	80.3 KB
013 Encoder Decoder Multi Head Attention.mp4	180.3 MB
013 Encoder Decoder Multi Head Attention_en.srt	25.0 KB
014 Final Decoder Linear And Softmax Layer.mp4	162.8 MB
014 Final Decoder Linear And Softmax Layer_en.srt	21.5 KB
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