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[FreeCourseSite.com] Udemy - 2021 Python for Machine Learning & Data Science Masterclass
magnet:?xt=urn:btih:9bb6f4ed1cc28fd5ac588c30af40d23b4eec5182&dn=[FreeCourseSite.com] Udemy - 2021 Python for Machine Learning & Data Science Masterclass
磁力链接详情
Hash值:
9bb6f4ed1cc28fd5ac588c30af40d23b4eec5182
点击数:
148
文件大小:
10.38 GB
文件数量:
209
创建日期:
2022-6-23 20:38
最后访问:
2024-7-22 10:28
访问标签:
FreeCourseSite
com
Udemy
-
2021
Python
for
Machine
Learning
&
Data
Science
Masterclass
文件列表详情
01 Introduction to Course/002 COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP!.mp4 24.55 MB
01 Introduction to Course/003 Anaconda Python and Jupyter Install and Setup.mp4 84.52 MB
01 Introduction to Course/005 Environment Setup.mp4 23.23 MB
02 OPTIONAL_ Python Crash Course/002 Python Crash Course - Part One.mp4 29.76 MB
02 OPTIONAL_ Python Crash Course/003 Python Crash Course - Part Two.mp4 25.85 MB
02 OPTIONAL_ Python Crash Course/004 Python Crash Course - Part Three.mp4 32.02 MB
02 OPTIONAL_ Python Crash Course/005 Python Crash Course - Exercise Questions.mp4 7.82 MB
02 OPTIONAL_ Python Crash Course/006 Python Crash Course - Exercise Solutions.mp4 33.49 MB
03 Machine Learning Pathway Overview/001 Machine Learning Pathway.mp4 40.54 MB
04 NumPy/001 Introduction to NumPy.mp4 7.88 MB
04 NumPy/002 NumPy Arrays.mp4 99.45 MB
04 NumPy/003 NumPy Indexing and Selection.mp4 39.64 MB
04 NumPy/004 NumPy Operations.mp4 36.04 MB
04 NumPy/005 NumPy Exercises.mp4 9.66 MB
04 NumPy/006 Numpy Exercises - Solutions.mp4 34.9 MB
05 Pandas/001 Introduction to Pandas.mp4 8.72 MB
05 Pandas/002 Series - Part One.mp4 28.63 MB
05 Pandas/003 Series - Part Two.mp4 26.13 MB
05 Pandas/004 DataFrames - Part One - Creating a DataFrame.mp4 97.4 MB
05 Pandas/005 DataFrames - Part Two - Basic Properties.mp4 40.26 MB
05 Pandas/006 DataFrames - Part Three - Working with Columns.mp4 84.07 MB
05 Pandas/007 DataFrames - Part Four - Working with Rows.mp4 72.57 MB
05 Pandas/008 Pandas - Conditional Filtering.mp4 69.23 MB
05 Pandas/009 Pandas - Useful Methods - Apply on Single Column.mp4 53.73 MB
05 Pandas/010 Pandas - Useful Methods - Apply on Multiple Columns.mp4 85.33 MB
05 Pandas/011 Pandas - Useful Methods - Statistical Information and Sorting.mp4 74.4 MB
05 Pandas/012 Missing Data - Overview.mp4 27.26 MB
05 Pandas/013 Missing Data - Pandas Operations.mp4 73.6 MB
05 Pandas/014 GroupBy Operations - Part One.mp4 86.92 MB
05 Pandas/015 GroupBy Operations - Part Two - MultiIndex.mp4 93.05 MB
05 Pandas/016 Combining DataFrames - Concatenation.mp4 36.84 MB
05 Pandas/017 Combining DataFrames - Inner Merge.mp4 40.28 MB
05 Pandas/018 Combining DataFrames - Left and Right Merge.mp4 16.43 MB
05 Pandas/019 Combining DataFrames - Outer Merge.mp4 22.19 MB
05 Pandas/020 Pandas - Text Methods for String Data.mp4 45.14 MB
05 Pandas/021 Pandas - Time Methods for Date and Time Data.mp4 80.22 MB
05 Pandas/022 Pandas Input and Output - CSV Files.mp4 37.13 MB
05 Pandas/023 Pandas Input and Output - HTML Tables.mp4 102.38 MB
05 Pandas/024 Pandas Input and Output - Excel Files.mp4 25.91 MB
05 Pandas/025 Pandas Input and Output - SQL Databases.mp4 96.18 MB
05 Pandas/026 Pandas Pivot Tables.mp4 128.74 MB
05 Pandas/027 Pandas Project Exercise Overview.mp4 39.38 MB
05 Pandas/028 Pandas Project Exercise Solutions.mp4 172.62 MB
06 Matplotlib/001 Introduction to Matplotlib.mp4 11.39 MB
06 Matplotlib/002 Matplotlib Basics.mp4 31.07 MB
06 Matplotlib/003 Matplotlib - Understanding the Figure Object.mp4 11.7 MB
06 Matplotlib/004 Matplotlib - Implementing Figures and Axes.mp4 34.86 MB
06 Matplotlib/005 Matplotlib - Figure Parameters.mp4 11.4 MB
06 Matplotlib/006 Matplotlib - Subplots Functionality.mp4 96.18 MB
06 Matplotlib/007 Matplotlib Styling - Legends.mp4 16.21 MB
06 Matplotlib/008 Matplotlib Styling - Colors and Styles.mp4 44.29 MB
06 Matplotlib/009 Advanced Matplotlib Commands (Optional).mp4 25.24 MB
06 Matplotlib/010 Matplotlib Exercise Questions Overview.mp4 48.94 MB
06 Matplotlib/011 Matplotlib Exercise Questions - Solutions.mp4 105.83 MB
07 Seaborn Data Visualizations/001 Introduction to Seaborn.mp4 10.53 MB
07 Seaborn Data Visualizations/002 Scatterplots with Seaborn.mp4 111.13 MB
07 Seaborn Data Visualizations/003 Distribution Plots - Part One - Understanding Plot Types.mp4 15.04 MB
07 Seaborn Data Visualizations/004 Distribution Plots - Part Two - Coding with Seaborn.mp4 44.41 MB
07 Seaborn Data Visualizations/005 Categorical Plots - Statistics within Categories - Understanding Plot Types.mp4 16 MB
07 Seaborn Data Visualizations/006 Categorical Plots - Statistics within Categories - Coding with Seaborn.mp4 51.61 MB
07 Seaborn Data Visualizations/007 Categorical Plots - Distributions within Categories - Understanding Plot Types.mp4 44.98 MB
07 Seaborn Data Visualizations/008 Categorical Plots - Distributions within Categories - Coding with Seaborn.mp4 84.59 MB
07 Seaborn Data Visualizations/009 Seaborn - Comparison Plots - Understanding the Plot Types.mp4 10.57 MB
07 Seaborn Data Visualizations/010 Seaborn - Comparison Plots - Coding with Seaborn.mp4 51.13 MB
07 Seaborn Data Visualizations/011 Seaborn Grid Plots.mp4 86.98 MB
07 Seaborn Data Visualizations/012 Seaborn - Matrix Plots.mp4 34.45 MB
07 Seaborn Data Visualizations/013 Seaborn Plot Exercises Overview.mp4 15.8 MB
07 Seaborn Data Visualizations/014 Seaborn Plot Exercises Solutions.mp4 105.67 MB
08 Data Analysis and Visualization Capstone Project Exercise/001 Capstone Project Overview.mp4 93.2 MB
08 Data Analysis and Visualization Capstone Project Exercise/002 Capstone Project Solutions - Part One.mp4 101.92 MB
08 Data Analysis and Visualization Capstone Project Exercise/003 Capstone Project Solutions - Part Two.mp4 106.21 MB
08 Data Analysis and Visualization Capstone Project Exercise/004 Capstone Project Solutions - Part Three.mp4 137.26 MB
09 Machine Learning Concepts Overview/001 Introduction to Machine Learning Overview Section.mp4 13.19 MB
09 Machine Learning Concepts Overview/002 Why Machine Learning_.mp4 21.01 MB
09 Machine Learning Concepts Overview/003 Types of Machine Learning Algorithms.mp4 18.11 MB
09 Machine Learning Concepts Overview/004 Supervised Machine Learning Process.mp4 33.53 MB
09 Machine Learning Concepts Overview/005 Companion Book - Introduction to Statistical Learning.mp4 9.68 MB
10 Linear Regression/001 Introduction to Linear Regression Section.mp4 3.38 MB
10 Linear Regression/002 Linear Regression - Algorithm History.mp4 54.71 MB
10 Linear Regression/003 Linear Regression - Understanding Ordinary Least Squares.mp4 73.28 MB
10 Linear Regression/004 Linear Regression - Cost Functions.mp4 16.64 MB
10 Linear Regression/005 Linear Regression - Gradient Descent.mp4 29.21 MB
10 Linear Regression/006 Python coding Simple Linear Regression.mp4 83.88 MB
10 Linear Regression/007 Overview of Scikit-Learn and Python.mp4 23.14 MB
10 Linear Regression/008 Linear Regression - Scikit-Learn Train Test Split.mp4 61.44 MB
10 Linear Regression/009 Linear Regression - Scikit-Learn Performance Evaluation - Regression.mp4 61.79 MB
10 Linear Regression/010 Linear Regression - Residual Plots.mp4 29.66 MB
10 Linear Regression/011 Linear Regression - Model Deployment and Coefficient Interpretation.mp4 81.24 MB
10 Linear Regression/012 Polynomial Regression - Theory and Motivation.mp4 22.26 MB
10 Linear Regression/013 Polynomial Regression - Creating Polynomial Features.mp4 40.08 MB
10 Linear Regression/014 Polynomial Regression - Training and Evaluation.mp4 36.31 MB
10 Linear Regression/015 Bias Variance Trade-Off.mp4 36.19 MB
10 Linear Regression/016 Polynomial Regression - Choosing Degree of Polynomial.mp4 55.73 MB
10 Linear Regression/017 Polynomial Regression - Model Deployment.mp4 23.24 MB
10 Linear Regression/018 Regularization Overview.mp4 13.07 MB
10 Linear Regression/019 Feature Scaling.mp4 24.36 MB
10 Linear Regression/020 Introduction to Cross Validation.mp4 29.28 MB
10 Linear Regression/021 Regularization Data Setup.mp4 15.43 MB
10 Linear Regression/022 L2 Regularization - Ridge Regression Theory.mp4 61.08 MB
10 Linear Regression/023 L2 Regularization - Ridge Regression - Python Implementation.mp4 89.37 MB
10 Linear Regression/024 L1 Regularization - Lasso Regression - Background and Implementation.mp4 94.55 MB
10 Linear Regression/025 L1 and L2 Regularization - Elastic Net.mp4 66.42 MB
10 Linear Regression/026 Linear Regression Project - Data Overview.mp4 16.95 MB
11 Feature Engineering and Data Preparation/002 Introduction to Feature Engineering and Data Preparation.mp4 40.68 MB
11 Feature Engineering and Data Preparation/003 Dealing with Outliers.mp4 120.68 MB
11 Feature Engineering and Data Preparation/004 Dealing with Missing Data _ Part One - Evaluation of Missing Data.mp4 31.43 MB
11 Feature Engineering and Data Preparation/005 Dealing with Missing Data _ Part Two - Filling or Dropping data based on Rows.mp4 117.6 MB
11 Feature Engineering and Data Preparation/006 Dealing with Missing Data _ Part 3 - Fixing data based on Columns.mp4 105.28 MB
11 Feature Engineering and Data Preparation/007 Dealing with Categorical Data - Encoding Options.mp4 58.93 MB
12 Cross Validation , Grid Search, and the Linear Regression Project/001 Section Overview and Introduction.mp4 9.95 MB
12 Cross Validation , Grid Search, and the Linear Regression Project/002 Cross Validation - Test _ Train Split.mp4 46.89 MB
12 Cross Validation , Grid Search, and the Linear Regression Project/003 Cross Validation - Test _ Validation _ Train Split.mp4 59.45 MB
12 Cross Validation , Grid Search, and the Linear Regression Project/004 Cross Validation - cross_val_score.mp4 44.51 MB
12 Cross Validation , Grid Search, and the Linear Regression Project/005 Cross Validation - cross_validate.mp4 45.08 MB
12 Cross Validation , Grid Search, and the Linear Regression Project/006 Grid Search.mp4 73.22 MB
12 Cross Validation , Grid Search, and the Linear Regression Project/007 Linear Regression Project Overview.mp4 23.55 MB
12 Cross Validation , Grid Search, and the Linear Regression Project/008 Linear Regression Project - Solutions.mp4 91.17 MB
13 Logistic Regression/002 Introduction to Logistic Regression Section.mp4 13.94 MB
13 Logistic Regression/003 Logistic Regression - Theory and Intuition - Part One_ The Logistic Function.mp4 17.35 MB
13 Logistic Regression/004 Logistic Regression - Theory and Intuition - Part Two_ Linear to Logistic.mp4 11.07 MB
13 Logistic Regression/005 Logistic Regression - Theory and Intuition - Linear to Logistic Math.mp4 36.05 MB
13 Logistic Regression/006 Logistic Regression - Theory and Intuition - Best fit with Maximum Likelihood.mp4 54.89 MB
13 Logistic Regression/007 Logistic Regression with Scikit-Learn - Part One - EDA.mp4 62.6 MB
13 Logistic Regression/008 Logistic Regression with Scikit-Learn - Part Two - Model Training.mp4 32.57 MB
13 Logistic Regression/009 Classification Metrics - Confusion Matrix and Accuracy.mp4 21.72 MB
13 Logistic Regression/010 Classification Metrics - Precison, Recall, F1-Score.mp4 23.42 MB
13 Logistic Regression/011 Classification Metrics - ROC Curves.mp4 16.09 MB
13 Logistic Regression/012 Logistic Regression with Scikit-Learn - Part Three - Performance Evaluation.mp4 63.65 MB
13 Logistic Regression/013 Multi-Class Classification with Logistic Regression - Part One - Data and EDA.mp4 37.38 MB
13 Logistic Regression/014 Multi-Class Classification with Logistic Regression - Part Two - Model.mp4 105.09 MB
13 Logistic Regression/015 Logistic Regression Exercise Project Overview.mp4 24.32 MB
13 Logistic Regression/016 Logistic Regression Project Exercise - Solutions.mp4 145.55 MB
14 KNN - K Nearest Neighbors/001 Introduction to KNN Section.mp4 4.97 MB
14 KNN - K Nearest Neighbors/002 KNN Classification - Theory and Intuition.mp4 23.56 MB
14 KNN - K Nearest Neighbors/003 KNN Coding with Python - Part One.mp4 61.61 MB
14 KNN - K Nearest Neighbors/004 KNN Coding with Python - Part Two - Choosing K.mp4 102.92 MB
14 KNN - K Nearest Neighbors/005 KNN Classification Project Exercise Overview.mp4 21.1 MB
14 KNN - K Nearest Neighbors/006 KNN Classification Project Exercise Solutions.mp4 105.05 MB
15 Support Vector Machines/001 Introduction to Support Vector Machines.mp4 4.34 MB
15 Support Vector Machines/002 History of Support Vector Machines.mp4 15.55 MB
15 Support Vector Machines/003 SVM - Theory and Intuition - Hyperplanes and Margins.mp4 35.31 MB
15 Support Vector Machines/004 SVM - Theory and Intuition - Kernel Intuition.mp4 13.36 MB
15 Support Vector Machines/005 SVM - Theory and Intuition - Kernel Trick and Mathematics.mp4 52.69 MB
15 Support Vector Machines/006 SVM with Scikit-Learn and Python - Classification Part One.mp4 46.29 MB
15 Support Vector Machines/007 SVM with Scikit-Learn and Python - Classification Part Two.mp4 83.18 MB
15 Support Vector Machines/008 SVM with Scikit-Learn and Python - Regression Tasks.mp4 76.32 MB
15 Support Vector Machines/009 Support Vector Machine Project Overview.mp4 34.83 MB
15 Support Vector Machines/010 Support Vector Machine Project Solutions.mp4 93.45 MB
16 Tree Based Methods_ Decision Tree Learning/001 Introduction to Tree Based Methods.mp4 2.61 MB
16 Tree Based Methods_ Decision Tree Learning/002 Decision Tree - History.mp4 35.59 MB
16 Tree Based Methods_ Decision Tree Learning/003 Decision Tree - Terminology.mp4 6.34 MB
16 Tree Based Methods_ Decision Tree Learning/004 Decision Tree - Understanding Gini Impurity.mp4 19.47 MB
16 Tree Based Methods_ Decision Tree Learning/005 Constructing Decision Trees with Gini Impurity - Part One.mp4 17.72 MB
16 Tree Based Methods_ Decision Tree Learning/006 Constructing Decision Trees with Gini Impurity - Part Two.mp4 28.21 MB
16 Tree Based Methods_ Decision Tree Learning/007 Coding Decision Trees - Part One - The Data.mp4 98.73 MB
16 Tree Based Methods_ Decision Tree Learning/008 Coding Decision Trees - Part Two -Creating the Model.mp4 115.85 MB
17 Random Forests/001 Introduction to Random Forests Section.mp4 4.1 MB
17 Random Forests/002 Random Forests - History and Motivation.mp4 24.01 MB
17 Random Forests/003 Random Forests - Key Hyperparameters.mp4 9.6 MB
17 Random Forests/004 Random Forests - Number of Estimators and Features in Subsets.mp4 27.33 MB
17 Random Forests/005 Random Forests - Bootstrapping and Out-of-Bag Error.mp4 43.38 MB
17 Random Forests/006 Coding Classification with Random Forest Classifier - Part One.mp4 52.11 MB
17 Random Forests/007 Coding Classification with Random Forest Classifier - Part Two.mp4 130.38 MB
17 Random Forests/008 Coding Regression with Random Forest Regressor - Part One - Data.mp4 13.71 MB
17 Random Forests/009 Coding Regression with Random Forest Regressor - Part Two - Basic Models.mp4 84.92 MB
17 Random Forests/010 Coding Regression with Random Forest Regressor - Part Three - Polynomials.mp4 45.61 MB
17 Random Forests/011 Coding Regression with Random Forest Regressor - Part Four - Advanced Models.mp4 50.66 MB
18 Boosting Methods/001 Introduction to Boosting Section.mp4 4.11 MB
18 Boosting Methods/002 Boosting Methods - Motivation and History.mp4 21.97 MB
18 Boosting Methods/003 AdaBoost Theory and Intuition.mp4 41.55 MB
18 Boosting Methods/004 AdaBoost Coding Part One - The Data.mp4 22.77 MB
18 Boosting Methods/005 AdaBoost Coding Part Two - The Model.mp4 63.12 MB
18 Boosting Methods/006 Gradient Boosting Theory.mp4 22.96 MB
18 Boosting Methods/007 Gradient Boosting Coding Walkthrough.mp4 57.98 MB
19 Supervised Learning Capstone Project - Cohort Analysis and Tree Based Methods/001 Introduction to Supervised Learning Capstone Project.mp4 73.3 MB
20 Naive Bayes Classification and Natural Language Processing (Supervised Learning)/001 Introduction to NLP and Naive Bayes Section.mp4 6.75 MB
20 Naive Bayes Classification and Natural Language Processing (Supervised Learning)/002 Naive Bayes Algorithm - Part One - Bayes Theorem.mp4 22.04 MB
20 Naive Bayes Classification and Natural Language Processing (Supervised Learning)/003 Naive Bayes Algorithm - Part Two - Model Algorithm.mp4 48.64 MB
20 Naive Bayes Classification and Natural Language Processing (Supervised Learning)/009 Text Classification Project Exercise Overview.mp4 30.53 MB
20 Naive Bayes Classification and Natural Language Processing (Supervised Learning)/010 Text Classification Project Exercise Solutions.mp4 108.07 MB
21 Unsupervised Learning/001 Unsupervised Learning Overview.mp4 31.73 MB
22 K-Means Clustering/001 Introduction to K-Means Clustering Section.mp4 4.57 MB
22 K-Means Clustering/002 Clustering General Overview.mp4 24.89 MB
22 K-Means Clustering/003 K-Means Clustering Theory.mp4 52.36 MB
22 K-Means Clustering/004 K-Means Clustering - Coding Part One.mp4 97.51 MB
22 K-Means Clustering/005 K-Means Clustering Coding Part Two.mp4 80.63 MB
22 K-Means Clustering/006 K-Means Clustering Coding Part Three.mp4 59.54 MB
22 K-Means Clustering/007 K-Means Color Quantization - Part One.mp4 80.36 MB
22 K-Means Clustering/008 K-Means Color Quantization - Part Two.mp4 64.75 MB
22 K-Means Clustering/009 K-Means Clustering Exercise Overview.mp4 59.33 MB
22 K-Means Clustering/010 K-Means Clustering Exercise Solution - Part One.mp4 79.72 MB
22 K-Means Clustering/011 K-Means Clustering Exercise Solution - Part Two.mp4 107.89 MB
22 K-Means Clustering/012 K-Means Clustering Exercise Solution - Part Three.mp4 62.47 MB
23 Hierarchical Clustering/001 Introduction to Hierarchical Clustering.mp4 5.81 MB
23 Hierarchical Clustering/002 Hierarchical Clustering - Theory and Intuition.mp4 51.94 MB
23 Hierarchical Clustering/003 Hierarchical Clustering - Coding Part One - Data and Visualization.mp4 114.83 MB
23 Hierarchical Clustering/004 Hierarchical Clustering - Coding Part Two - Scikit-Learn.mp4 208.67 MB
24 DBSCAN - Density-based spatial clustering of applications with noise/001 Introduction to DBSCAN Section.mp4 5.92 MB
24 DBSCAN - Density-based spatial clustering of applications with noise/002 DBSCAN - Theory and Intuition.mp4 109.1 MB
24 DBSCAN - Density-based spatial clustering of applications with noise/003 DBSCAN versus K-Means Clustering.mp4 66.74 MB
24 DBSCAN - Density-based spatial clustering of applications with noise/004 DBSCAN - Hyperparameter Theory.mp4 16.46 MB
24 DBSCAN - Density-based spatial clustering of applications with noise/005 DBSCAN - Hyperparameter Tuning Methods.mp4 105.09 MB
24 DBSCAN - Density-based spatial clustering of applications with noise/006 DBSCAN - Outlier Project Exercise Overview.mp4 50.18 MB
24 DBSCAN - Density-based spatial clustering of applications with noise/007 DBSCAN - Outlier Project Exercise Solutions.mp4 127.96 MB
25 PCA - Principal Component Analysis and Manifold Learning/001 Introduction to Principal Component Analysis.mp4 6.15 MB
25 PCA - Principal Component Analysis and Manifold Learning/002 PCA Theory and Intuition - Part One.mp4 29.73 MB
25 PCA - Principal Component Analysis and Manifold Learning/003 PCA Theory and Intuition - Part Two.mp4 19.06 MB
25 PCA - Principal Component Analysis and Manifold Learning/004 PCA - Manual Implementation in Python.mp4 95.14 MB
25 PCA - Principal Component Analysis and Manifold Learning/005 PCA - SciKit-Learn.mp4 74.1 MB
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