Udemy Python for Machine Learning Data Science Masterclass 2021 | 449AAEED336E6979371AD34EC1EBDF3BA98B8DDA

Udemy Python for Machine Learning Data Science Masterclass 2021

Name	Udemy - Python for Machine Learning & Data Science Masterclass (9.2021)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	12.3 GB
Total Files	510
Last Seen
Hash	449AAEED336E6979371AD34EC1EBDF3BA98B8DDA

/01 - Introduction to Course/
001 Welcome to the Course_.html	1.7 KB
01 - Introduction to Course/
002 COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP_.mp4	7.6 MB
002 COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP_.srt	7.3 KB
003 Anaconda Python and Jupyter Install and Setup.mp4	88.6 MB
003 Anaconda Python and Jupyter Install and Setup.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.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.srt	25.2 KB
003 Python Crash Course - Part Two.mp4	60.4 MB
003 Python Crash Course - Part Two.srt	18.5 KB
004 Python Crash Course - Part Three.mp4	33.6 MB
004 Python Crash Course - Part Three.srt	17.0 KB
005 Python Crash Course - Exercise Questions.mp4	3.6 MB
005 Python Crash Course - Exercise Questions.srt	2.6 KB
006 Python Crash Course - Exercise Solutions.mp4	51.1 MB
006 Python Crash Course - Exercise Solutions.srt	13.8 KB
03 - Machine Learning Pathway Overview/
001 Machine Learning Pathway.mp4	14.8 MB
001 Machine Learning Pathway.srt	16.2 KB
04 - NumPy/
001 Introduction to NumPy.mp4	3.5 MB
001 Introduction to NumPy.srt	3.1 KB
002 NumPy Arrays.mp4	104.3 MB
002 NumPy Arrays.srt	32.7 KB
003 NumPy Indexing and Selection.mp4	41.6 MB
003 NumPy Indexing and Selection.srt	16.6 KB
004 NumPy Operations.mp4	37.8 MB
004 NumPy Operations.srt	12.3 KB
005 NumPy Exercises.mp4	10.1 MB
005 NumPy Exercises.srt	2.1 KB
006 Numpy Exercises - Solutions.mp4	36.6 MB
006 Numpy Exercises - Solutions.srt	11.1 KB
05 - Pandas/
001 Introduction to Pandas.mp4	7.0 MB
001 Introduction to Pandas.srt	7.4 KB
002 Series - Part One.mp4	30.0 MB
002 Series - Part One.srt	13.7 KB
003 Series - Part Two.mp4	27.4 MB
003 Series - Part Two.srt	15.7 KB
004 DataFrames - Part One - Creating a DataFrame.mp4	102.2 MB
004 DataFrames - Part One - Creating a DataFrame.srt	29.7 KB
005 DataFrames - Part Two - Basic Properties.mp4	42.2 MB
005 DataFrames - Part Two - Basic Properties.srt	13.6 KB
006 DataFrames - Part Three - Working with Columns.mp4	88.2 MB
006 DataFrames - Part Three - Working with Columns.srt	21.1 KB
007 DataFrames - Part Four - Working with Rows.mp4	76.1 MB
007 DataFrames - Part Four - Working with Rows.srt	21.6 KB
008 Pandas - Conditional Filtering.mp4	72.6 MB
008 Pandas - Conditional Filtering.srt	27.8 KB
009 Pandas - Useful Methods - Apply on Single Column.mp4	56.3 MB
009 Pandas - Useful Methods - Apply on Single Column.srt	20.7 KB
010 Pandas - Useful Methods - Apply on Multiple Columns.mp4	89.5 MB
010 Pandas - Useful Methods - Apply on Multiple Columns.srt	26.6 KB
011 Pandas - Useful Methods - Statistical Information and Sorting.mp4	78.0 MB
011 Pandas - Useful Methods - Statistical Information and Sorting.srt	24.0 KB
012 Missing Data - Overview.mp4	28.6 MB
012 Missing Data - Overview.srt	18.8 KB
013 Missing Data - Pandas Operations.mp4	77.2 MB
013 Missing Data - Pandas Operations.srt	28.1 KB
014 GroupBy Operations - Part One.mp4	91.2 MB
014 GroupBy Operations - Part One.srt	21.9 KB
015 GroupBy Operations - Part Two - MultiIndex.mp4	97.4 MB
015 GroupBy Operations - Part Two - MultiIndex.srt	21.4 KB
016 Combining DataFrames - Concatenation.mp4	38.6 MB
016 Combining DataFrames - Concatenation.srt	15.4 KB
017 Combining DataFrames - Inner Merge.mp4	42.2 MB
017 Combining DataFrames - Inner Merge.srt	19.0 KB
018 Combining DataFrames - Left and Right Merge.mp4	17.2 MB
018 Combining DataFrames - Left and Right Merge.srt	9.3 KB
019 Combining DataFrames - Outer Merge.mp4	23.3 MB
019 Combining DataFrames - Outer Merge.srt	14.9 KB
020 Pandas - Text Methods for String Data.mp4	47.3 MB
020 Pandas - Text Methods for String Data.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.srt	32.5 KB
022 Pandas Input and Output - CSV Files.mp4	39.0 MB
022 Pandas Input and Output - CSV Files.srt	17.0 KB
023 Pandas Input and Output - HTML Tables.mp4	107.3 MB
023 Pandas Input and Output - HTML Tables.srt	22.9 KB
024 Pandas Input and Output - Excel Files.mp4	27.1 MB
024 Pandas Input and Output - Excel Files.srt	11.1 KB
025 Pandas Input and Output - SQL Databases.mp4	100.6 MB
025 Pandas Input and Output - SQL Databases.srt	30.1 KB
026 Pandas Pivot Tables.mp4	135.4 MB
026 Pandas Pivot Tables.srt	33.0 KB
027 Pandas Project Exercise Overview.mp4	41.3 MB
027 Pandas Project Exercise Overview.srt	9.8 KB
028 Pandas Project Exercise Solutions.mp4	180.9 MB
028 Pandas Project Exercise Solutions.srt	39.7 KB
06 - Matplotlib/
001 Introduction to Matplotlib.mp4	6.9 MB
001 Introduction to Matplotlib.srt	6.9 KB
002 Matplotlib Basics.mp4	32.6 MB
002 Matplotlib Basics.srt	20.1 KB
003 Matplotlib - Understanding the Figure Object.mp4	12.3 MB
003 Matplotlib - Understanding the Figure Object.srt	11.8 KB
004 Matplotlib - Implementing Figures and Axes.mp4	36.6 MB
004 Matplotlib - Implementing Figures and Axes.srt	21.5 KB
005 Matplotlib - Figure Parameters.mp4	13.7 MB
005 Matplotlib - Figure Parameters.srt	7.8 KB
006 Matplotlib - Subplots Functionality.mp4	101.3 MB
006 Matplotlib - Subplots Functionality.srt	29.3 KB
007 Matplotlib Styling - Legends.mp4	17.0 MB
007 Matplotlib Styling - Legends.srt	10.6 KB
008 Matplotlib Styling - Colors and Styles.mp4	46.4 MB
008 Matplotlib Styling - Colors and Styles.srt	21.6 KB
009 Advanced Matplotlib Commands (Optional).mp4	26.4 MB
009 Advanced Matplotlib Commands (Optional).srt	6.7 KB
010 Matplotlib Exercise Questions Overview.mp4	51.4 MB
010 Matplotlib Exercise Questions Overview.srt	9.6 KB
011 Matplotlib Exercise Questions - Solutions.mp4	111.0 MB
011 Matplotlib Exercise Questions - Solutions.srt	25.1 KB
07 - Seaborn Data Visualizations/
001 Introduction to Seaborn.mp4	6.0 MB
001 Introduction to Seaborn.srt	6.7 KB
002 Scatterplots with Seaborn.mp4	116.7 MB
002 Scatterplots with Seaborn.srt	30.4 KB
003 Distribution Plots - Part One - Understanding Plot Types.mp4	15.8 MB
003 Distribution Plots - Part One - Understanding Plot Types.srt	15.4 KB
004 Distribution Plots - Part Two - Coding with Seaborn.mp4	62.1 MB
004 Distribution Plots - Part Two - Coding with Seaborn.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.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.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.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.srt	28.9 KB
009 Seaborn - Comparison Plots - Understanding the Plot Types.mp4	11.1 MB
009 Seaborn - Comparison Plots - Understanding the Plot Types.srt	8.9 KB
010 Seaborn - Comparison Plots - Coding with Seaborn.mp4	53.6 MB
010 Seaborn - Comparison Plots - Coding with Seaborn.srt	16.1 KB
011 Seaborn Grid Plots.mp4	91.2 MB
011 Seaborn Grid Plots.srt	21.0 KB
012 Seaborn - Matrix Plots.mp4	64.5 MB
012 Seaborn - Matrix Plots.srt	21.6 KB
013 Seaborn Plot Exercises Overview.mp4	50.2 MB
013 Seaborn Plot Exercises Overview.srt	11.5 KB
014 Seaborn Plot Exercises Solutions.mp4	110.9 MB
014 Seaborn Plot Exercises Solutions.srt	22.9 KB
08 - Data Analysis and Visualization Capstone Project Exercise/
001 Capstone Project Overview.mp4	32.6 MB
001 Capstone Project Overview.srt	21.1 KB
002 Capstone Project Solutions - Part One.mp4	116.0 MB
002 Capstone Project Solutions - Part One.srt	27.5 KB
003 Capstone Project Solutions - Part Two.mp4	111.3 MB
003 Capstone Project Solutions - Part Two.srt	24.0 KB
004 Capstone Project Solutions - Part Three.mp4	144.1 MB
004 Capstone Project Solutions - Part Three.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.srt	8.8 KB
002 Why Machine Learning_.mp4	22.1 MB
002 Why Machine Learning_.srt	15.0 KB
003 Types of Machine Learning Algorithms.mp4	19.0 MB
003 Types of Machine Learning Algorithms.srt	11.9 KB
004 Supervised Machine Learning Process.mp4	35.2 MB
004 Supervised Machine Learning Process.srt	20.2 KB
005 Companion Book - Introduction to Statistical Learning.mp4	5.4 MB
005 Companion Book - Introduction to Statistical Learning.srt	4.8 KB
10 - Linear Regression/
001 Introduction to Linear Regression Section.mp4	2.7 MB
001 Introduction to Linear Regression Section.srt	2.7 KB
002 Linear Regression - Algorithm History.mp4	57.5 MB
002 Linear Regression - Algorithm History.srt	13.4 KB
003 Linear Regression - Understanding Ordinary Least Squares.mp4	90.6 MB
003 Linear Regression - Understanding Ordinary Least Squares.srt	23.1 KB
004 Linear Regression - Cost Functions.mp4	17.4 MB
004 Linear Regression - Cost Functions.srt	11.7 KB
005 Linear Regression - Gradient Descent.mp4	30.6 MB
005 Linear Regression - Gradient Descent.srt	17.1 KB
006 Python coding Simple Linear Regression.mp4	73.5 MB
006 Python coding Simple Linear Regression.srt	28.8 KB
007 Overview of Scikit-Learn and Python.mp4	33.0 MB
007 Overview of Scikit-Learn and Python.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.srt	24.3 KB
009 Linear Regression - Scikit-Learn Performance Evaluation - Regression.mp4	56.0 MB
009 Linear Regression - Scikit-Learn Performance Evaluation - Regression.srt	23.6 KB
010 Linear Regression - Residual Plots.mp4	46.2 MB
010 Linear Regression - Residual Plots.srt	20.7 KB
011 Linear Regression - Model Deployment and Coefficient Interpretation.mp4	85.1 MB
011 Linear Regression - Model Deployment and Coefficient Interpretation.srt	26.2 KB
012 Polynomial Regression - Theory and Motivation.mp4	23.3 MB
012 Polynomial Regression - Theory and Motivation.srt	11.5 KB
013 Polynomial Regression - Creating Polynomial Features.mp4	42.0 MB
013 Polynomial Regression - Creating Polynomial Features.srt	16.8 KB
014 Polynomial Regression - Training and Evaluation.mp4	38.1 MB
014 Polynomial Regression - Training and Evaluation.srt	14.5 KB
015 Bias Variance Trade-Off.mp4	37.9 MB
015 Bias Variance Trade-Off.srt	16.3 KB
016 Polynomial Regression - Choosing Degree of Polynomial.mp4	58.4 MB
016 Polynomial Regression - Choosing Degree of Polynomial.srt	20.4 KB
017 Polynomial Regression - Model Deployment.mp4	24.4 MB
017 Polynomial Regression - Model Deployment.srt	8.6 KB
018 Regularization Overview.mp4	16.3 MB
018 Regularization Overview.srt	10.6 KB
019 Feature Scaling.mp4	25.5 MB
019 Feature Scaling.srt	15.2 KB
020 Introduction to Cross Validation.mp4	34.6 MB
020 Introduction to Cross Validation.srt	20.3 KB
021 Regularization Data Setup.mp4	21.1 MB
021 Regularization Data Setup.srt	12.7 KB
022 L2 Regularization - Ridge Regression Theory.mp4	64.3 MB
022 L2 Regularization - Ridge Regression Theory.srt	21.2 KB
023 L2 Regularization - Ridge Regression - Python Implementation.mp4	93.7 MB
023 L2 Regularization - Ridge Regression - Python Implementation.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.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.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.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.srt	24.7 KB
003 Dealing with Outliers.mp4	108.3 MB
003 Dealing with Outliers.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.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.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.srt	37.6 KB
007 Dealing with Categorical Data - Encoding Options.mp4	61.7 MB
007 Dealing with Categorical Data - Encoding Options.srt	20.6 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.srt	5.2 KB
002 Cross Validation - Test _ Train Split.mp4	49.1 MB
002 Cross Validation - Test _ Train Split.srt	17.9 KB
003 Cross Validation - Test _ Validation _ Train Split.mp4	62.3 MB
003 Cross Validation - Test _ Validation _ Train Split.srt	22.2 KB
004 Cross Validation - cross_val_score.mp4	46.6 MB
004 Cross Validation - cross_val_score.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.srt	11.5 KB
006 Grid Search.mp4	76.7 MB
006 Grid Search.srt	19.7 KB
007 Linear Regression Project Overview.mp4	24.8 MB
007 Linear Regression Project Overview.srt	6.0 KB
008 Linear Regression Project - Solutions.mp4	95.7 MB
008 Linear Regression Project - Solutions.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.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.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.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.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.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.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.srt	9.8 KB
009 Classification Metrics - Confusion Matrix and Accuracy.mp4	22.8 MB
009 Classification Metrics - Confusion Matrix and Accuracy.srt	14.3 KB
010 Classification Metrics - Precison, Recall, F1-Score.mp4	34.8 MB
010 Classification Metrics - Precison, Recall, F1-Score.srt	8.5 KB
011 Classification Metrics - ROC Curves.mp4	16.9 MB
011 Classification Metrics - ROC Curves.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.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.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.srt	24.4 KB
015 Logistic Regression Exercise Project Overview.mp4	25.5 MB
015 Logistic Regression Exercise Project Overview.srt	6.6 KB
016 Logistic Regression Project Exercise - Solutions.mp4	169.1 MB
016 Logistic Regression Project Exercise - Solutions.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.srt	3.7 KB
002 KNN Classification - Theory and Intuition.mp4	24.7 MB
002 KNN Classification - Theory and Intuition.srt	17.3 KB
003 KNN Coding with Python - Part One.mp4	64.5 MB
003 KNN Coding with Python - Part One.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.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.srt	5.4 KB
006 KNN Classification Project Exercise Solutions.mp4	110.1 MB
006 KNN Classification Project Exercise Solutions.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.srt	2.4 KB
002 History of Support Vector Machines.mp4	16.3 MB
002 History of Support Vector Machines.srt	6.7 KB
003 SVM - Theory and Intuition - Hyperplanes and Margins.mp4	50.1 MB
003 SVM - Theory and Intuition - Hyperplanes and Margins.srt	19.0 KB
004 SVM - Theory and Intuition - Kernel Intuition.mp4	10.3 MB
004 SVM - Theory and Intuition - Kernel Intuition.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.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.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.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.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.srt	7.0 KB
010 Support Vector Machine Project Solutions.mp4	97.9 MB
010 Support Vector Machine Project Solutions.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.srt	2.3 KB
002 Decision Tree - History.mp4	37.3 MB
002 Decision Tree - History.srt	13.5 KB
003 Decision Tree - Terminology.mp4	7.6 MB
003 Decision Tree - Terminology.srt	6.6 KB
004 Decision Tree - Understanding Gini Impurity.mp4	20.4 MB
004 Decision Tree - Understanding Gini Impurity.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.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.srt	16.8 KB
007 Coding Decision Trees - Part One - The Data.mp4	103.5 MB
007 Coding Decision Trees - Part One - The Data.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.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.srt	2.9 KB
002 Random Forests - History and Motivation.mp4	25.2 MB
002 Random Forests - History and Motivation.srt	17.6 KB
003 Random Forests - Key Hyperparameters.mp4	8.7 MB
003 Random Forests - Key Hyperparameters.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.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.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.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.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.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.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.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.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.srt	2.7 KB
002 Boosting Methods - Motivation and History.mp4	23.0 MB
002 Boosting Methods - Motivation and History.srt	9.2 KB
003 AdaBoost Theory and Intuition.mp4	43.5 MB
003 AdaBoost Theory and Intuition.srt	29.6 KB
004 AdaBoost Coding Part One - The Data.mp4	44.3 MB
004 AdaBoost Coding Part One - The Data.srt	17.1 KB
005 AdaBoost Coding Part Two - The Model.mp4	66.2 MB
005 AdaBoost Coding Part Two - The Model.srt	27.2 KB
006 Gradient Boosting Theory.mp4	24.1 MB
006 Gradient Boosting Theory.srt	16.5 KB
007 Gradient Boosting Coding Walkthrough.mp4	60.7 MB
007 Gradient Boosting Coding Walkthrough.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 - Cohort Analysis and Tree Based Methods/
001 Introduction to Supervised Learning Capstone Project.mp4	31.3 MB
001 Introduction to Supervised Learning Capstone Project.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.srt	30.4 KB
003 Solution Walkthrough - Supervised Learning Project - Cohort Analysis.mp4	136.5 MB
003 Solution Walkthrough - Supervised Learning Project - Cohort Analysis.srt	39.7 KB
004 Solution Walkthrough - Supervised Learning Project - Tree Models.mp4	119.8 MB
004 Solution Walkthrough - Supervised Learning Project - Tree Models.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 (Supervised Learning)/
001 Introduction to NLP and Naive Bayes Section.mp4	4.4 MB
001 Introduction to NLP and Naive Bayes Section.srt	3.8 KB
002 Naive Bayes Algorithm - Part One - Bayes Theorem.mp4	23.1 MB
002 Naive Bayes Algorithm - Part One - Bayes Theorem.srt	12.1 KB
003 Naive Bayes Algorithm - Part Two - Model Algorithm.mp4	51.0 MB
003 Naive Bayes Algorithm - Part Two - Model Algorithm.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.srt	16.4 KB
005 Feature Extraction from Text - Coding Count Vectorization Manually.mp4	65.9 MB
005 Feature Extraction from Text - Coding Count Vectorization Manually.srt	27.9 KB
006 Feature Extraction from Text - Coding with Scikit-Learn.mp4	52.8 MB
006 Feature Extraction from Text - Coding with Scikit-Learn.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.srt	16.8 KB
008 Natural Language Processing - Classification of Text - Part Two.mp4	36.5 MB
008 Natural Language Processing - Classification of Text - Part Two.srt	15.7 KB
009 Text Classification Project Exercise Overview.mp4	32.0 MB
009 Text Classification Project Exercise Overview.srt	8.0 KB
010 Text Classification Project Exercise Solutions.mp4	105.5 MB
010 Text Classification Project Exercise Solutions.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.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.srt	3.6 KB
002 Clustering General Overview.mp4	26.1 MB
002 Clustering General Overview.srt	16.9 KB
003 K-Means Clustering Theory.mp4	55.0 MB
003 K-Means Clustering Theory.srt	17.7 KB
004 K-Means Clustering - Coding Part One.mp4	102.7 MB
004 K-Means Clustering - Coding Part One.srt	31.1 KB
005 K-Means Clustering Coding Part Two.mp4	84.8 MB
005 K-Means Clustering Coding Part Two.srt	27.2 KB
006 K-Means Clustering Coding Part Three.mp4	62.7 MB
006 K-Means Clustering Coding Part Three.srt	21.9 KB
007 K-Means Color Quantization - Part One.mp4	84.5 MB
007 K-Means Color Quantization - Part One.srt	20.9 KB
008 K-Means Color Quantization - Part Two.mp4	68.2 MB
008 K-Means Color Quantization - Part Two.srt	21.8 KB
009 K-Means Clustering Exercise Overview.mp4	62.4 MB
009 K-Means Clustering Exercise Overview.srt	13.8 KB
010 K-Means Clustering Exercise Solution - Part One.mp4	83.8 MB
010 K-Means Clustering Exercise Solution - Part One.srt	21.6 KB
011 K-Means Clustering Exercise Solution - Part Two.mp4	113.5 MB
011 K-Means Clustering Exercise Solution - Part Two.srt	24.1 KB
012 K-Means Clustering Exercise Solution - Part Three.mp4	65.5 MB
012 K-Means Clustering Exercise Solution - Part Three.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.srt	1.2 KB
002 Hierarchical Clustering - Theory and Intuition.mp4	54.6 MB
002 Hierarchical Clustering - Theory and Intuition.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.srt	26.0 KB
004 Hierarchical Clustering - Coding Part Two - Scikit-Learn.mp4	219.4 MB
004 Hierarchical Clustering - Coding Part Two - Scikit-Learn.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.srt	1.4 KB
002 DBSCAN - Theory and Intuition.mp4	114.4 MB
002 DBSCAN - Theory and Intuition.srt	27.1 KB
003 DBSCAN versus K-Means Clustering.mp4	69.9 MB
003 DBSCAN versus K-Means Clustering.srt	17.8 KB
004 DBSCAN - Hyperparameter Theory.mp4	14.5 MB
004 DBSCAN - Hyperparameter Theory.srt	11.0 KB
005 DBSCAN - Hyperparameter Tuning Methods.mp4	110.2 MB
005 DBSCAN - Hyperparameter Tuning Methods.srt	33.4 KB
006 DBSCAN - Outlier Project Exercise Overview.mp4	52.7 MB
006 DBSCAN - Outlier Project Exercise Overview.srt	10.2 KB
007 DBSCAN - Outlier Project Exercise Solutions.mp4	134.1 MB
007 DBSCAN - Outlier Project Exercise Solutions.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.srt	4.1 KB
002 PCA Theory and Intuition - Part One.mp4	31.2 MB
002 PCA Theory and Intuition - Part One.srt	16.0 KB
003 PCA Theory and Intuition - Part Two.mp4	20.0 MB
003 PCA Theory and Intuition - Part Two.srt	16.8 KB
004 PCA - Manual Implementation in Python.mp4	99.7 MB
004 PCA - Manual Implementation in Python.srt	26.9 KB
005 PCA - SciKit-Learn.mp4	77.7 MB
005 PCA - SciKit-Learn.srt	17.7 KB
006 PCA - Project Exercise Overview.mp4	55.3 MB
006 PCA - Project Exercise Overview.srt	12.2 KB
007 PCA - Project Exercise Solution.mp4	125.3 MB
007 PCA - Project Exercise Solution.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.srt	3.6 KB
002 Model Deployment Considerations.mp4	19.2 MB
002 Model Deployment Considerations.srt	10.8 KB
003 Model Persistence.mp4	115.1 MB
003 Model Persistence.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.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.srt	26.7 KB
007 Testing the API.mp4	34.8 MB
007 Testing the API.srt	12.5 KB
Total files 510