Tutorialsplanet NET Udemy 2022 Python for Machine Learning Data Science Masterclass

Tutorialsplanet NET Udemy 2022 Python for Machine Learning Data Science Masterclass

Name	[Tutorialsplanet.NET] Udemy - 2022 Python for Machine Learning & Data Science Masterclass	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	12.3 GB
Total Files	515
Last Seen
Hash	1F792304A9C54CA10904F35D679983939027C19C

/0. Websites you may like/
[Tutorialsplanet.NET].url	0.1 KB
/01 - Introduction to Course/
001 Welcome to the Course_.html	1.7 KB
002 COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP_.mp4	7.6 MB
002 COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP___en.srt	7.3 KB
003 Anaconda Python and Jupyter Install and Setup.mp4	88.6 MB
003 Anaconda Python and Jupyter Install and Setup__en.srt	22.1 KB
004 Note on Environment Setup - Please read me_.html	0.9 KB
005 Environment Setup.mp4	37.4 MB
005 Environment Setup__en.srt	14.8 KB
28813464-requirements.txt	0.2 KB
33985574-UNZIP-FOR-NOTEBOOKS-FINAL.zip	70.4 MB
33985614-UNZIP-FOR-NOTEBOOKS-FINAL.zip	70.4 MB
external-assets-links.txt	0.1 KB
/02 - OPTIONAL_ Python Crash Course/
001 OPTIONAL_ Python Crash Course.html	0.5 KB
002 Python Crash Course - Part One.mp4	31.2 MB
002 Python Crash Course - Part One__en.srt	25.2 KB
003 Python Crash Course - Part Two.mp4	60.4 MB
003 Python Crash Course - Part Two__en.srt	18.5 KB
004 Python Crash Course - Part Three.mp4	33.6 MB
004 Python Crash Course - Part Three__en.srt	17.0 KB
005 Python Crash Course - Exercise Questions.mp4	3.6 MB
005 Python Crash Course - Exercise Questions__en.srt	2.6 KB
006 Python Crash Course - Exercise Solutions.mp4	51.1 MB
006 Python Crash Course - Exercise Solutions__en.srt	13.8 KB
[Tutorialsplanet.NET].url	0.1 KB
/03 - Machine Learning Pathway Overview/
001 Machine Learning Pathway.mp4	14.8 MB
001 Machine Learning Pathway__en.srt	16.2 KB
/04 - NumPy/
001 Introduction to NumPy.mp4	3.5 MB
001 Introduction to NumPy__en.srt	3.1 KB
002 NumPy Arrays.mp4	104.3 MB
002 NumPy Arrays__en.srt	32.7 KB
003 NumPy Indexing and Selection.mp4	41.6 MB
003 NumPy Indexing and Selection__en.srt	16.6 KB
004 NumPy Operations.mp4	37.8 MB
004 NumPy Operations__en.srt	12.3 KB
005 NumPy Exercises.mp4	10.1 MB
005 NumPy Exercises__en.srt	2.1 KB
006 Numpy Exercises - Solutions.mp4	36.6 MB
006 Numpy Exercises - Solutions__en.srt	11.1 KB
/05 - Pandas/
001 Introduction to Pandas.mp4	7.0 MB
001 Introduction to Pandas__en.srt	7.4 KB
002 Series - Part One.mp4	30.0 MB
002 Series - Part One__en.srt	13.7 KB
003 Series - Part Two.mp4	27.4 MB
003 Series - Part Two__en.srt	15.7 KB
004 DataFrames - Part One - Creating a DataFrame.mp4	102.2 MB
004 DataFrames - Part One - Creating a DataFrame__en.srt	29.7 KB
005 DataFrames - Part Two - Basic Properties.mp4	42.2 MB
005 DataFrames - Part Two - Basic Properties__en.srt	13.6 KB
006 DataFrames - Part Three - Working with Columns.mp4	88.2 MB
006 DataFrames - Part Three - Working with Columns__en.srt	21.1 KB
007 DataFrames - Part Four - Working with Rows.mp4	76.1 MB
007 DataFrames - Part Four - Working with Rows__en.srt	21.6 KB
008 Pandas - Conditional Filtering.mp4	72.6 MB
008 Pandas - Conditional Filtering__en.srt	27.8 KB
009 Pandas - Useful Methods - Apply on Single Column.mp4	56.3 MB
009 Pandas - Useful Methods - Apply on Single Column__en.srt	20.7 KB
010 Pandas - Useful Methods - Apply on Multiple Columns.mp4	89.5 MB
010 Pandas - Useful Methods - Apply on Multiple Columns__en.srt	26.6 KB
011 Pandas - Useful Methods - Statistical Information and Sorting.mp4	78.0 MB
011 Pandas - Useful Methods - Statistical Information and Sorting__en.srt	24.0 KB
012 Missing Data - Overview.mp4	28.6 MB
012 Missing Data - Overview__en.srt	18.8 KB
013 Missing Data - Pandas Operations.mp4	77.2 MB
013 Missing Data - Pandas Operations__en.srt	28.1 KB
014 GroupBy Operations - Part One.mp4	91.2 MB
014 GroupBy Operations - Part One__en.srt	21.9 KB
015 GroupBy Operations - Part Two - MultiIndex.mp4	97.4 MB
015 GroupBy Operations - Part Two - MultiIndex__en.srt	21.4 KB
016 Combining DataFrames - Concatenation.mp4	38.6 MB
016 Combining DataFrames - Concatenation__en.srt	15.4 KB
017 Combining DataFrames - Inner Merge.mp4	42.2 MB
017 Combining DataFrames - Inner Merge__en.srt	19.0 KB
018 Combining DataFrames - Left and Right Merge.mp4	17.2 MB
018 Combining DataFrames - Left and Right Merge__en.srt	9.3 KB
019 Combining DataFrames - Outer Merge.mp4	23.3 MB
019 Combining DataFrames - Outer Merge__en.srt	14.9 KB
020 Pandas - Text Methods for String Data.mp4	47.3 MB
020 Pandas - Text Methods for String Data__en.srt	24.5 KB
021 Pandas - Time Methods for Date and Time Data.mp4	84.1 MB
021 Pandas - Time Methods for Date and Time Data__en.srt	32.5 KB
022 Pandas Input and Output - CSV Files.mp4	39.0 MB
022 Pandas Input and Output - CSV Files__en.srt	17.0 KB
023 Pandas Input and Output - HTML Tables.mp4	107.3 MB
023 Pandas Input and Output - HTML Tables__en.srt	22.9 KB
024 Pandas Input and Output - Excel Files.mp4	27.1 MB
024 Pandas Input and Output - Excel Files__en.srt	11.1 KB
025 Pandas Input and Output - SQL Databases.mp4	100.6 MB
025 Pandas Input and Output - SQL Databases__en.srt	30.1 KB
026 Pandas Pivot Tables.mp4	135.4 MB
026 Pandas Pivot Tables__en.srt	33.0 KB
027 Pandas Project Exercise Overview.mp4	41.3 MB
027 Pandas Project Exercise Overview__en.srt	9.8 KB
028 Pandas Project Exercise Solutions.mp4	180.9 MB
028 Pandas Project Exercise Solutions__en.srt	39.7 KB
/06 - Matplotlib/
001 Introduction to Matplotlib.mp4	6.9 MB
001 Introduction to Matplotlib__en.srt	6.9 KB
002 Matplotlib Basics.mp4	32.6 MB
002 Matplotlib Basics__en.srt	20.1 KB
003 Matplotlib - Understanding the Figure Object.mp4	12.3 MB
003 Matplotlib - Understanding the Figure Object__en.srt	11.8 KB
004 Matplotlib - Implementing Figures and Axes.mp4	36.6 MB
004 Matplotlib - Implementing Figures and Axes__en.srt	21.5 KB
005 Matplotlib - Figure Parameters.mp4	13.7 MB
005 Matplotlib - Figure Parameters__en.srt	7.8 KB
006 Matplotlib - Subplots Functionality.mp4	101.3 MB
006 Matplotlib - Subplots Functionality__en.srt	29.3 KB
007 Matplotlib Styling - Legends.mp4	17.0 MB
007 Matplotlib Styling - Legends__en.srt	10.6 KB
008 Matplotlib Styling - Colors and Styles.mp4	46.4 MB
008 Matplotlib Styling - Colors and Styles__en.srt	21.6 KB
009 Advanced Matplotlib Commands (Optional).mp4	26.4 MB
009 Advanced Matplotlib Commands (Optional)__en.srt	6.7 KB
010 Matplotlib Exercise Questions Overview.mp4	51.4 MB
010 Matplotlib Exercise Questions Overview__en.srt	9.6 KB
011 Matplotlib Exercise Questions - Solutions.mp4	111.0 MB
011 Matplotlib Exercise Questions - Solutions__en.srt	25.1 KB
/07 - Seaborn Data Visualizations/
001 Introduction to Seaborn.mp4	6.0 MB
001 Introduction to Seaborn__en.srt	6.7 KB
002 Scatterplots with Seaborn.mp4	116.7 MB
002 Scatterplots with Seaborn__en.srt	30.4 KB
003 Distribution Plots - Part One - Understanding Plot Types.mp4	15.8 MB
003 Distribution Plots - Part One - Understanding Plot Types__en.srt	15.4 KB
004 Distribution Plots - Part Two - Coding with Seaborn.mp4	62.1 MB
004 Distribution Plots - Part Two - Coding with Seaborn__en.srt	25.4 KB
005 Categorical Plots - Statistics within Categories - Understanding Plot Types.mp4	16.8 MB
005 Categorical Plots - Statistics within Categories - Understanding Plot Types__en.srt	9.0 KB
006 Categorical Plots - Statistics within Categories - Coding with Seaborn.mp4	54.2 MB
006 Categorical Plots - Statistics within Categories - Coding with Seaborn__en.srt	15.0 KB
007 Categorical Plots - Distributions within Categories - Understanding Plot Types.mp4	47.1 MB
007 Categorical Plots - Distributions within Categories - Understanding Plot Types__en.srt	20.6 KB
008 Categorical Plots - Distributions within Categories - Coding with Seaborn.mp4	88.7 MB
008 Categorical Plots - Distributions within Categories - Coding with Seaborn__en.srt	28.9 KB
009 Seaborn - Comparison Plots - Understanding the Plot Types.mp4	11.1 MB
009 Seaborn - Comparison Plots - Understanding the Plot Types__en.srt	8.9 KB
010 Seaborn - Comparison Plots - Coding with Seaborn.mp4	53.6 MB
010 Seaborn - Comparison Plots - Coding with Seaborn__en.srt	16.1 KB
011 Seaborn Grid Plots.mp4	91.2 MB
011 Seaborn Grid Plots__en.srt	21.0 KB
012 Seaborn - Matrix Plots.mp4	64.5 MB
012 Seaborn - Matrix Plots__en.srt	21.6 KB
013 Seaborn Plot Exercises Overview.mp4	50.2 MB
013 Seaborn Plot Exercises Overview__en.srt	11.5 KB
014 Seaborn Plot Exercises Solutions.mp4	110.9 MB
014 Seaborn Plot Exercises Solutions__en.srt	22.9 KB
/08 - Data Analysis and Visualization Capstone Project Exercise/
001 Capstone Project Overview.mp4	32.6 MB
001 Capstone Project Overview__en.srt	21.1 KB
002 Capstone Project Solutions - Part One.mp4	116.0 MB
002 Capstone Project Solutions - Part One__en.srt	27.5 KB
003 Capstone Project Solutions - Part Two.mp4	111.3 MB
003 Capstone Project Solutions - Part Two__en.srt	24.0 KB
004 Capstone Project Solutions - Part Three.mp4	144.1 MB
004 Capstone Project Solutions - Part Three__en.srt	31.6 KB
/09 - Machine Learning Concepts Overview/
001 Introduction to Machine Learning Overview Section.mp4	13.8 MB
001 Introduction to Machine Learning Overview Section__en.srt	8.8 KB
002 Why Machine Learning_.mp4	22.1 MB
002 Why Machine Learning___en.srt	15.0 KB
003 Types of Machine Learning Algorithms.mp4	19.0 MB
003 Types of Machine Learning Algorithms__en.srt	11.9 KB
004 Supervised Machine Learning Process.mp4	35.2 MB
004 Supervised Machine Learning Process__en.srt	20.2 KB
005 Companion Book - Introduction to Statistical Learning.mp4	5.4 MB
005 Companion Book - Introduction to Statistical Learning__en.srt	4.8 KB
/10 - Linear Regression/
001 Introduction to Linear Regression Section.mp4	2.7 MB
001 Introduction to Linear Regression Section__en.srt	2.7 KB
002 Linear Regression - Algorithm History.mp4	57.5 MB
002 Linear Regression - Algorithm History__en.srt	13.4 KB
003 Linear Regression - Understanding Ordinary Least Squares.mp4	90.6 MB
003 Linear Regression - Understanding Ordinary Least Squares__en.srt	23.1 KB
004 Linear Regression - Cost Functions.mp4	17.4 MB
004 Linear Regression - Cost Functions__en.srt	11.7 KB
005 Linear Regression - Gradient Descent.mp4	30.6 MB
005 Linear Regression - Gradient Descent__en.srt	17.1 KB
006 Python coding Simple Linear Regression.mp4	73.5 MB
006 Python coding Simple Linear Regression__en.srt	28.8 KB
007 Overview of Scikit-Learn and Python.mp4	33.0 MB
007 Overview of Scikit-Learn and Python__en.srt	10.4 KB
007 Overview of Scikit-Learn and Python_en.vtt	11.2 KB
008 Linear Regression - Scikit-Learn Train Test Split.mp4	64.4 MB
008 Linear Regression - Scikit-Learn Train Test Split__en.srt	24.3 KB
009 Linear Regression - Scikit-Learn Performance Evaluation - Regression.mp4	56.0 MB
009 Linear Regression - Scikit-Learn Performance Evaluation - Regression__en.srt	23.6 KB
010 Linear Regression - Residual Plots.mp4	46.2 MB
010 Linear Regression - Residual Plots__en.srt	20.7 KB
011 Linear Regression - Model Deployment and Coefficient Interpretation.mp4	85.1 MB
011 Linear Regression - Model Deployment and Coefficient Interpretation__en.srt	26.2 KB
012 Polynomial Regression - Theory and Motivation.mp4	23.3 MB
012 Polynomial Regression - Theory and Motivation__en.srt	11.5 KB
013 Polynomial Regression - Creating Polynomial Features.mp4	42.0 MB
013 Polynomial Regression - Creating Polynomial Features__en.srt	16.8 KB
014 Polynomial Regression - Training and Evaluation.mp4	38.1 MB
014 Polynomial Regression - Training and Evaluation__en.srt	14.5 KB
015 Bias Variance Trade-Off.mp4	37.9 MB
015 Bias Variance Trade-Off__en.srt	16.3 KB
016 Polynomial Regression - Choosing Degree of Polynomial.mp4	58.4 MB
016 Polynomial Regression - Choosing Degree of Polynomial__en.srt	20.4 KB
017 Polynomial Regression - Model Deployment.mp4	24.4 MB
017 Polynomial Regression - Model Deployment__en.srt	8.6 KB
018 Regularization Overview.mp4	16.3 MB
018 Regularization Overview__en.srt	10.6 KB
019 Feature Scaling.mp4	25.5 MB
019 Feature Scaling__en.srt	15.2 KB
020 Introduction to Cross Validation.mp4	34.6 MB
020 Introduction to Cross Validation__en.srt	20.3 KB
021 Regularization Data Setup.mp4	21.1 MB
021 Regularization Data Setup__en.srt	12.7 KB
022 L2 Regularization - Ridge Regression Theory.mp4	64.3 MB
022 L2 Regularization - Ridge Regression Theory__en.srt	21.2 KB
023 L2 Regularization - Ridge Regression - Python Implementation.mp4	93.7 MB
023 L2 Regularization - Ridge Regression - Python Implementation__en.srt	11.2 KB
023 L2 Regularization - Ridge Regression - Python Implementation_en.vtt	23.5 KB
024 L1 Regularization - Lasso Regression - Background and Implementation.mp4	99.2 MB
024 L1 Regularization - Lasso Regression - Background and Implementation__en.srt	5.5 KB
024 L1 Regularization - Lasso Regression - Background and Implementation_en.vtt	20.1 KB
025 L1 and L2 Regularization - Elastic Net.mp4	69.6 MB
025 L1 and L2 Regularization - Elastic Net__en.srt	17.4 KB
025 L1 and L2 Regularization - Elastic Net_en.vtt	23.2 KB
026 Linear Regression Project - Data Overview.mp4	17.8 MB
026 Linear Regression Project - Data Overview__en.srt	7.9 KB
/11 - Feature Engineering and Data Preparation/
001 A note from Jose on Feature Engineering and Data Preparation.html	1.0 KB
002 Introduction to Feature Engineering and Data Preparation.mp4	37.9 MB
002 Introduction to Feature Engineering and Data Preparation__en.srt	24.7 KB
003 Dealing with Outliers.mp4	108.3 MB
003 Dealing with Outliers__en.srt	42.2 KB
004 Dealing with Missing Data _ Part One - Evaluation of Missing Data.mp4	20.0 MB
004 Dealing with Missing Data _ Part One - Evaluation of Missing Data__en.srt	17.4 KB
005 Dealing with Missing Data _ Part Two - Filling or Dropping data based on Rows.mp4	123.3 MB
005 Dealing with Missing Data _ Part Two - Filling or Dropping data based on Rows__en.srt	32.2 KB
006 Dealing with Missing Data _ Part 3 - Fixing data based on Columns.mp4	110.3 MB
006 Dealing with Missing Data _ Part 3 - Fixing data based on Columns__en.srt	37.6 KB
007 Dealing with Categorical Data - Encoding Options.mp4	61.7 MB
007 Dealing with Categorical Data - Encoding Options__en.srt	20.6 KB
[Tutorialsplanet.NET].url	0.1 KB
/12 - Cross Validation , Grid Search, and the Linear Regression Project/
001 Section Overview and Introduction.mp4	5.9 MB
001 Section Overview and Introduction__en.srt	5.2 KB
002 Cross Validation - Test _ Train Split.mp4	49.1 MB
002 Cross Validation - Test _ Train Split__en.srt	17.9 KB
003 Cross Validation - Test _ Validation _ Train Split.mp4	62.3 MB
003 Cross Validation - Test _ Validation _ Train Split__en.srt	22.2 KB
004 Cross Validation - cross_val_score.mp4	46.6 MB
004 Cross Validation - cross_val_score__en.srt	8.3 KB
004 Cross Validation - cross_val_score_en.vtt	15.6 KB
005 Cross Validation - cross_validate.mp4	47.2 MB
005 Cross Validation - cross_validate__en.srt	11.5 KB
006 Grid Search.mp4	76.7 MB
006 Grid Search__en.srt	19.7 KB
007 Linear Regression Project Overview.mp4	24.8 MB
007 Linear Regression Project Overview__en.srt	6.0 KB
008 Linear Regression Project - Solutions.mp4	95.7 MB
008 Linear Regression Project - Solutions__en.srt	9.0 KB
008 Linear Regression Project - Solutions_en.vtt	16.3 KB
/13 - Logistic Regression/
001 Early Bird Note on Downloading .zip for Logistic Regression Notes.html	0.5 KB
002 Introduction to Logistic Regression Section.mp4	14.6 MB
002 Introduction to Logistic Regression Section__en.srt	8.6 KB
003 Logistic Regression - Theory and Intuition - Part One_ The Logistic Function.mp4	18.2 MB
003 Logistic Regression - Theory and Intuition - Part One_ The Logistic Function__en.srt	8.3 KB
004 Logistic Regression - Theory and Intuition - Part Two_ Linear to Logistic.mp4	8.4 MB
004 Logistic Regression - Theory and Intuition - Part Two_ Linear to Logistic__en.srt	7.4 KB
005 Logistic Regression - Theory and Intuition - Linear to Logistic Math.mp4	37.8 MB
005 Logistic Regression - Theory and Intuition - Linear to Logistic Math__en.srt	25.4 KB
006 Logistic Regression - Theory and Intuition - Best fit with Maximum Likelihood.mp4	57.6 MB
006 Logistic Regression - Theory and Intuition - Best fit with Maximum Likelihood__en.srt	23.5 KB
007 Logistic Regression with Scikit-Learn - Part One - EDA.mp4	65.5 MB
007 Logistic Regression with Scikit-Learn - Part One - EDA__en.srt	22.4 KB
008 Logistic Regression with Scikit-Learn - Part Two - Model Training.mp4	34.2 MB
008 Logistic Regression with Scikit-Learn - Part Two - Model Training__en.srt	9.8 KB
009 Classification Metrics - Confusion Matrix and Accuracy.mp4	22.8 MB
009 Classification Metrics - Confusion Matrix and Accuracy__en.srt	14.3 KB
010 Classification Metrics - Precison, Recall, F1-Score.mp4	34.8 MB
010 Classification Metrics - Precison, Recall, F1-Score__en.srt	8.5 KB
011 Classification Metrics - ROC Curves.mp4	16.9 MB
011 Classification Metrics - ROC Curves__en.srt	11.3 KB
012 Logistic Regression with Scikit-Learn - Part Three - Performance Evaluation.mp4	59.8 MB
012 Logistic Regression with Scikit-Learn - Part Three - Performance Evaluation__en.srt	24.0 KB
013 Multi-Class Classification with Logistic Regression - Part One - Data and EDA.mp4	39.2 MB
013 Multi-Class Classification with Logistic Regression - Part One - Data and EDA__en.srt	12.3 KB
014 Multi-Class Classification with Logistic Regression - Part Two - Model.mp4	110.2 MB
014 Multi-Class Classification with Logistic Regression - Part Two - Model__en.srt	24.4 KB
015 Logistic Regression Exercise Project Overview.mp4	25.5 MB
015 Logistic Regression Exercise Project Overview__en.srt	6.6 KB
016 Logistic Regression Project Exercise - Solutions.mp4	169.1 MB
016 Logistic Regression Project Exercise - Solutions__en.srt	14.7 KB
016 Logistic Regression Project Exercise - Solutions_en.vtt	31.6 KB
29304858-11-Logistic-Regression-Models.zip	2.1 MB
/14 - KNN - K Nearest Neighbors/
001 Introduction to KNN Section.mp4	3.8 MB
001 Introduction to KNN Section__en.srt	3.7 KB
002 KNN Classification - Theory and Intuition.mp4	24.7 MB
002 KNN Classification - Theory and Intuition__en.srt	17.3 KB
003 KNN Coding with Python - Part One.mp4	64.5 MB
003 KNN Coding with Python - Part One__en.srt	11.3 KB
003 KNN Coding with Python - Part One_en.vtt	19.8 KB
004 KNN Coding with Python - Part Two - Choosing K.mp4	107.9 MB
004 KNN Coding with Python - Part Two - Choosing K__en.srt	4.0 KB
004 KNN Coding with Python - Part Two - Choosing K_en.vtt	31.4 KB
005 KNN Classification Project Exercise Overview.mp4	22.2 MB
005 KNN Classification Project Exercise Overview__en.srt	5.4 KB
006 KNN Classification Project Exercise Solutions.mp4	110.1 MB
006 KNN Classification Project Exercise Solutions__en.srt	8.8 KB
006 KNN Classification Project Exercise Solutions_en.vtt	19.0 KB
29434428-12-K-Nearest-Neighbors.zip	1.4 MB
/15 - Support Vector Machines/
001 Introduction to Support Vector Machines.mp4	2.9 MB
001 Introduction to Support Vector Machines__en.srt	2.4 KB
002 History of Support Vector Machines.mp4	16.3 MB
002 History of Support Vector Machines__en.srt	6.7 KB
003 SVM - Theory and Intuition - Hyperplanes and Margins.mp4	50.1 MB
003 SVM - Theory and Intuition - Hyperplanes and Margins__en.srt	19.0 KB
004 SVM - Theory and Intuition - Kernel Intuition.mp4	10.3 MB
004 SVM - Theory and Intuition - Kernel Intuition__en.srt	7.3 KB
005 SVM - Theory and Intuition - Kernel Trick and Mathematics.mp4	55.2 MB
005 SVM - Theory and Intuition - Kernel Trick and Mathematics__en.srt	30.0 KB
006 SVM with Scikit-Learn and Python - Classification Part One.mp4	48.5 MB
006 SVM with Scikit-Learn and Python - Classification Part One__en.srt	16.8 KB
007 SVM with Scikit-Learn and Python - Classification Part Two.mp4	95.0 MB
007 SVM with Scikit-Learn and Python - Classification Part Two__en.srt	21.2 KB
007 SVM with Scikit-Learn and Python - Classification Part Two_en.vtt	21.5 KB
008 SVM with Scikit-Learn and Python - Regression Tasks.mp4	80.0 MB
008 SVM with Scikit-Learn and Python - Regression Tasks__en.srt	26.3 KB
008 SVM with Scikit-Learn and Python - Regression Tasks_en.vtt	26.8 KB
009 Support Vector Machine Project Overview.mp4	36.5 MB
009 Support Vector Machine Project Overview__en.srt	7.0 KB
010 Support Vector Machine Project Solutions.mp4	97.9 MB
010 Support Vector Machine Project Solutions__en.srt	13.1 KB
010 Support Vector Machine Project Solutions_en.vtt	23.0 KB
29902052-13-Support-Vector-Machines.zip	1.6 MB
/16 - Tree Based Methods_ Decision Tree Learning/
001 Introduction to Tree Based Methods.mp4	2.4 MB
001 Introduction to Tree Based Methods__en.srt	2.3 KB
002 Decision Tree - History.mp4	37.3 MB
002 Decision Tree - History__en.srt	13.5 KB
003 Decision Tree - Terminology.mp4	7.6 MB
003 Decision Tree - Terminology__en.srt	6.6 KB
004 Decision Tree - Understanding Gini Impurity.mp4	20.4 MB
004 Decision Tree - Understanding Gini Impurity__en.srt	11.4 KB
005 Constructing Decision Trees with Gini Impurity - Part One.mp4	18.6 MB
005 Constructing Decision Trees with Gini Impurity - Part One__en.srt	11.8 KB
006 Constructing Decision Trees with Gini Impurity - Part Two.mp4	54.9 MB
006 Constructing Decision Trees with Gini Impurity - Part Two__en.srt	16.8 KB
007 Coding Decision Trees - Part One - The Data.mp4	103.5 MB
007 Coding Decision Trees - Part One - The Data__en.srt	30.0 KB
008 Coding Decision Trees - Part Two -Creating the Model.mp4	121.4 MB
008 Coding Decision Trees - Part Two -Creating the Model__en.srt	33.5 KB
30205020-14-Decision-Trees.zip	1.9 MB
/17 - Random Forests/
001 Introduction to Random Forests Section.mp4	3.0 MB
001 Introduction to Random Forests Section__en.srt	2.9 KB
002 Random Forests - History and Motivation.mp4	25.2 MB
002 Random Forests - History and Motivation__en.srt	17.6 KB
003 Random Forests - Key Hyperparameters.mp4	8.7 MB
003 Random Forests - Key Hyperparameters__en.srt	4.6 KB
004 Random Forests - Number of Estimators and Features in Subsets.mp4	28.6 MB
004 Random Forests - Number of Estimators and Features in Subsets__en.srt	16.6 KB
005 Random Forests - Bootstrapping and Out-of-Bag Error.mp4	34.3 MB
005 Random Forests - Bootstrapping and Out-of-Bag Error__en.srt	18.4 KB
006 Coding Classification with Random Forest Classifier - Part One.mp4	54.6 MB
006 Coding Classification with Random Forest Classifier - Part One__en.srt	10.2 KB
006 Coding Classification with Random Forest Classifier - Part One_en.vtt	16.2 KB
007 Coding Classification with Random Forest Classifier - Part Two.mp4	136.7 MB
007 Coding Classification with Random Forest Classifier - Part Two__en.srt	20.5 KB
007 Coding Classification with Random Forest Classifier - Part Two_en.vtt	28.6 KB
008 Coding Regression with Random Forest Regressor - Part One - Data.mp4	14.3 MB
008 Coding Regression with Random Forest Regressor - Part One - Data__en.srt	7.0 KB
009 Coding Regression with Random Forest Regressor - Part Two - Basic Models.mp4	89.1 MB
009 Coding Regression with Random Forest Regressor - Part Two - Basic Models__en.srt	20.9 KB
010 Coding Regression with Random Forest Regressor - Part Three - Polynomials.mp4	47.7 MB
010 Coding Regression with Random Forest Regressor - Part Three - Polynomials__en.srt	15.7 KB
011 Coding Regression with Random Forest Regressor - Part Four - Advanced Models.mp4	53.1 MB
011 Coding Regression with Random Forest Regressor - Part Four - Advanced Models__en.srt	15.8 KB
30930956-15-Random-Forests.zip	4.1 MB
30930966-data-banknote-authentication.csv	46.5 KB
/18 - Boosting Methods/
001 Introduction to Boosting Section.mp4	3.1 MB
001 Introduction to Boosting Section__en.srt	2.7 KB
002 Boosting Methods - Motivation and History.mp4	23.0 MB
002 Boosting Methods - Motivation and History__en.srt	9.2 KB
003 AdaBoost Theory and Intuition.mp4	43.5 MB
003 AdaBoost Theory and Intuition__en.srt	29.6 KB
004 AdaBoost Coding Part One - The Data.mp4	44.3 MB
004 AdaBoost Coding Part One - The Data__en.srt	17.1 KB
005 AdaBoost Coding Part Two - The Model.mp4	66.2 MB
005 AdaBoost Coding Part Two - The Model__en.srt	27.2 KB
006 Gradient Boosting Theory.mp4	24.1 MB
006 Gradient Boosting Theory__en.srt	16.5 KB
007 Gradient Boosting Coding Walkthrough.mp4	60.7 MB
007 Gradient Boosting Coding Walkthrough__en.srt	9.1 KB
007 Gradient Boosting Coding Walkthrough_en.vtt	17.9 KB
31286608-16-Boosted-Trees.zip	940.0 KB
31286610-mushrooms.csv	374.0 KB
/19 - Supervised Learning Capstone Project/
001 Introduction to Supervised Learning Capstone Project.mp4	31.3 MB
001 Introduction to Supervised Learning Capstone Project__en.srt	26.3 KB
002 Solution Walkthrough - Supervised Learning Project - Data and EDA.mp4	111.3 MB
002 Solution Walkthrough - Supervised Learning Project - Data and EDA__en.srt	30.4 KB
003 Solution Walkthrough - Supervised Learning Project - Cohort Analysis.mp4	136.5 MB
003 Solution Walkthrough - Supervised Learning Project - Cohort Analysis__en.srt	39.7 KB
004 Solution Walkthrough - Supervised Learning Project - Tree Models.mp4	119.8 MB
004 Solution Walkthrough - Supervised Learning Project - Tree Models__en.srt	4.3 KB
004 Solution Walkthrough - Supervised Learning Project - Tree Models_en.vtt	30.1 KB
31389398-17-Supervised-Learning-Capstone-Project.zip	7.4 MB
31389400-Telco-Customer-Churn.csv	976.5 KB
/20 - Naive Bayes Classification and Natural Language Processing/
001 Introduction to NLP and Naive Bayes Section.mp4	4.4 MB
001 Introduction to NLP and Naive Bayes Section__en.srt	3.8 KB
002 Naive Bayes Algorithm - Part One - Bayes Theorem.mp4	23.1 MB
002 Naive Bayes Algorithm - Part One - Bayes Theorem__en.srt	12.1 KB
003 Naive Bayes Algorithm - Part Two - Model Algorithm.mp4	51.0 MB
003 Naive Bayes Algorithm - Part Two - Model Algorithm__en.srt	27.0 KB
004 Feature Extraction from Text - Part One - Theory and Intuition.mp4	30.8 MB
004 Feature Extraction from Text - Part One - Theory and Intuition__en.srt	0.0 KB
005 Feature Extraction from Text - Coding Count Vectorization Manually.mp4	0.0 KB
005 Feature Extraction from Text - Coding Count Vectorization Manually__en.srt	0.0 KB
006 Feature Extraction from Text - Coding with Scikit-Learn.mp4	52.8 MB
006 Feature Extraction from Text - Coding with Scikit-Learn__en.srt	17.1 KB
007 Natural Language Processing - Classification of Text - Part One.mp4	29.6 MB
007 Natural Language Processing - Classification of Text - Part One__en.srt	0.0 KB
008 Natural Language Processing - Classification of Text - Part Two.mp4	36.5 MB
008 Natural Language Processing - Classification of Text - Part Two__en.srt	0.0 KB
009 Text Classification Project Exercise Overview.mp4	32.0 MB
009 Text Classification Project Exercise Overview__en.srt	8.0 KB
010 Text Classification Project Exercise Solutions.mp4	105.5 MB
010 Text Classification Project Exercise Solutions__en.srt	19.9 KB
010 Text Classification Project Exercise Solutions_en.vtt	21.8 KB
31640094-18-Naive-Bayes-and-NLP.zip	197.1 KB
31640102-airline-tweets.csv	3.4 MB
31640132-moviereviews.csv	7.6 MB
/21 - Unsupervised Learning/
001 Unsupervised Learning Overview.mp4	14.4 MB
001 Unsupervised Learning Overview__en.srt	13.2 KB
/22 - K-Means Clustering/
001 Introduction to K-Means Clustering Section.mp4	3.7 MB
001 Introduction to K-Means Clustering Section__en.srt	3.6 KB
002 Clustering General Overview.mp4	26.1 MB
002 Clustering General Overview__en.srt	16.9 KB
003 K-Means Clustering Theory.mp4	55.0 MB
003 K-Means Clustering Theory__en.srt	17.7 KB
004 K-Means Clustering - Coding Part One.mp4	102.7 MB
004 K-Means Clustering - Coding Part One__en.srt	31.1 KB
005 K-Means Clustering Coding Part Two.mp4	84.8 MB
005 K-Means Clustering Coding Part Two__en.srt	27.2 KB
006 K-Means Clustering Coding Part Three.mp4	62.7 MB
006 K-Means Clustering Coding Part Three__en.srt	21.9 KB
007 K-Means Color Quantization - Part One.mp4	84.5 MB
007 K-Means Color Quantization - Part One__en.srt	20.9 KB
008 K-Means Color Quantization - Part Two.mp4	68.2 MB
008 K-Means Color Quantization - Part Two__en.srt	21.8 KB
009 K-Means Clustering Exercise Overview.mp4	62.4 MB
009 K-Means Clustering Exercise Overview__en.srt	13.8 KB
010 K-Means Clustering Exercise Solution - Part One.mp4	83.8 MB
010 K-Means Clustering Exercise Solution - Part One__en.srt	21.6 KB
011 K-Means Clustering Exercise Solution - Part Two.mp4	113.5 MB
011 K-Means Clustering Exercise Solution - Part Two__en.srt	24.1 KB
012 K-Means Clustering Exercise Solution - Part Three.mp4	65.5 MB
012 K-Means Clustering Exercise Solution - Part Three__en.srt	12.4 KB
32407448-20-Kmeans-Clustering.zip	6.1 MB
32407452-bank-full.csv	5.2 MB
32407456-CIA-Country-Facts.csv	33.5 KB
32407460-country-iso-codes.csv	8.1 KB
33555798-palm-trees.jpg	176.9 KB
/23 - Hierarchical Clustering/
001 Introduction to Hierarchical Clustering.mp4	1.8 MB
001 Introduction to Hierarchical Clustering__en.srt	1.2 KB
002 Hierarchical Clustering - Theory and Intuition.mp4	54.6 MB
002 Hierarchical Clustering - Theory and Intuition__en.srt	17.7 KB
003 Hierarchical Clustering - Coding Part One - Data and Visualization.mp4	120.6 MB
003 Hierarchical Clustering - Coding Part One - Data and Visualization__en.srt	26.0 KB
004 Hierarchical Clustering - Coding Part Two - Scikit-Learn.mp4	219.4 MB
004 Hierarchical Clustering - Coding Part Two - Scikit-Learn__en.srt	43.3 KB
33028500-21-Hierarchical-Clustering.zip	636.5 KB
33028506-cluster-mpg.csv	21.3 KB
/24 - DBSCAN - Density-based spatial clustering of applications with noise/
001 Introduction to DBSCAN Section.mp4	1.9 MB
001 Introduction to DBSCAN Section__en.srt	1.4 KB
002 DBSCAN - Theory and Intuition.mp4	114.4 MB
002 DBSCAN - Theory and Intuition__en.srt	27.1 KB
003 DBSCAN versus K-Means Clustering.mp4	69.9 MB
003 DBSCAN versus K-Means Clustering__en.srt	17.8 KB
004 DBSCAN - Hyperparameter Theory.mp4	14.5 MB
004 DBSCAN - Hyperparameter Theory__en.srt	11.0 KB
005 DBSCAN - Hyperparameter Tuning Methods.mp4	110.2 MB
005 DBSCAN - Hyperparameter Tuning Methods__en.srt	33.4 KB
006 DBSCAN - Outlier Project Exercise Overview.mp4	52.7 MB
006 DBSCAN - Outlier Project Exercise Overview__en.srt	10.2 KB
007 DBSCAN - Outlier Project Exercise Solutions.mp4	134.1 MB
007 DBSCAN - Outlier Project Exercise Solutions__en.srt	39.0 KB
33643014-22-DBSCAN.zip	3.7 MB
33643060-cluster-circles.csv	61.3 KB
33643066-wholesome-customers-data.csv	15.0 KB
33643070-cluster-two-blobs-outliers.csv	39.2 KB
33643072-cluster-two-blobs.csv	39.2 KB
33643080-cluster-blobs.csv	57.2 KB
33643082-cluster-moons.csv	60.1 KB
external-assets-links.txt	0.1 KB
/25 - PCA - Principal Component Analysis and Manifold Learning/
001 Introduction to Principal Component Analysis.mp4	5.3 MB
001 Introduction to Principal Component Analysis__en.srt	4.1 KB
002 PCA Theory and Intuition - Part One.mp4	31.2 MB
002 PCA Theory and Intuition - Part One__en.srt	16.0 KB
003 PCA Theory and Intuition - Part Two.mp4	20.0 MB
003 PCA Theory and Intuition - Part Two__en.srt	16.8 KB
004 PCA - Manual Implementation in Python.mp4	99.7 MB
004 PCA - Manual Implementation in Python__en.srt	26.9 KB
005 PCA - SciKit-Learn.mp4	77.7 MB
005 PCA - SciKit-Learn__en.srt	17.7 KB
006 PCA - Project Exercise Overview.mp4	55.3 MB
006 PCA - Project Exercise Overview__en.srt	12.2 KB
007 PCA - Project Exercise Solution.mp4	125.3 MB
007 PCA - Project Exercise Solution__en.srt	26.3 KB
33912190-digits.csv	497.2 KB
33912194-cancer-tumor-data-features.csv	120.8 KB
33912220-23-PCA-Principal-Component-Analysis.zip	4.1 MB
/26 - Model Deployment/
001 Model Deployment Section Overview.mp4	4.4 MB
001 Model Deployment Section Overview__en.srt	3.6 KB
002 Model Deployment Considerations.mp4	19.2 MB
002 Model Deployment Considerations__en.srt	10.8 KB
003 Model Persistence.mp4	115.1 MB
003 Model Persistence__en.srt	3.1 KB
003 Model Persistence_en.vtt	28.8 KB
004 Model Deployment as an API - General Overview.mp4	18.3 MB
004 Model Deployment as an API - General Overview__en.srt	11.9 KB
005 Note on Upcoming Video.html	0.2 KB
006 Model API - Creating the Script.mp4	70.5 MB
006 Model API - Creating the Script__en.srt	26.7 KB
007 Testing the API.mp4	34.8 MB
007 Testing the API__en.srt	12.5 KB
[Tutorialsplanet.NET].url	0.1 KB
/
[Tutorialsplanet.NET].url	0.1 KB
Total files 515