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[GigaCourse.Com] Udemy - 2022 Python for Machine Learning & Data Science Masterclass
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2022-9-1 12:16
2024-9-5 15:18
205
11.31 GB
225
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GigaCourse
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Udemy
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2022
Python
for
Machine
Learning
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Science
Masterclass
文件列表
01 - Introduction to Course/002 COURSE OVERVIEW LECTURE - PLEASE DO NOT SKIP_.mp4
7.22MB
01 - Introduction to Course/003 Anaconda Python and Jupyter Install and Setup.mp4
84.53MB
01 - Introduction to Course/005 Environment Setup.mp4
35.71MB
02 - OPTIONAL_ Python Crash Course/002 Python Crash Course - Part One.mp4
29.74MB
02 - OPTIONAL_ Python Crash Course/003 Python Crash Course - Part Two.mp4
57.63MB
02 - OPTIONAL_ Python Crash Course/004 Python Crash Course - Part Three.mp4
32.01MB
02 - OPTIONAL_ Python Crash Course/005 Python Crash Course - Exercise Questions.mp4
3.41MB
02 - OPTIONAL_ Python Crash Course/006 Python Crash Course - Exercise Solutions.mp4
48.7MB
03 - Machine Learning Pathway Overview/001 Machine Learning Pathway.mp4
14.1MB
04 - NumPy/001 Introduction to NumPy.mp4
3.37MB
04 - NumPy/002 NumPy Arrays.mp4
99.45MB
04 - NumPy/003 NumPy Indexing and Selection.mp4
39.63MB
04 - NumPy/004 NumPy Operations.mp4
36.06MB
04 - NumPy/005 NumPy Exercises.mp4
9.64MB
04 - NumPy/006 Numpy Exercises - Solutions.mp4
34.88MB
05 - Pandas/001 Introduction to Pandas.mp4
6.7MB
05 - Pandas/002 Series - Part One.mp4
28.62MB
05 - Pandas/003 Series - Part Two.mp4
26.12MB
05 - Pandas/004 DataFrames - Part One - Creating a DataFrame.mp4
97.48MB
05 - Pandas/005 DataFrames - Part Two - Basic Properties.mp4
40.28MB
05 - Pandas/006 DataFrames - Part Three - Working with Columns.mp4
84.08MB
05 - Pandas/007 DataFrames - Part Four - Working with Rows.mp4
72.59MB
05 - Pandas/008 Pandas - Conditional Filtering.mp4
69.21MB
05 - Pandas/009 Pandas - Useful Methods - Apply on Single Column.mp4
53.72MB
05 - Pandas/010 Pandas - Useful Methods - Apply on Multiple Columns.mp4
85.32MB
05 - Pandas/011 Pandas - Useful Methods - Statistical Information and Sorting.mp4
74.37MB
05 - Pandas/012 Missing Data - Overview.mp4
27.24MB
05 - Pandas/013 Missing Data - Pandas Operations.mp4
73.6MB
05 - Pandas/014 GroupBy Operations - Part One.mp4
86.96MB
05 - Pandas/015 GroupBy Operations - Part Two - MultiIndex.mp4
92.86MB
05 - Pandas/016 Combining DataFrames - Concatenation.mp4
36.84MB
05 - Pandas/017 Combining DataFrames - Inner Merge.mp4
40.27MB
05 - Pandas/018 Combining DataFrames - Left and Right Merge.mp4
16.4MB
05 - Pandas/019 Combining DataFrames - Outer Merge.mp4
22.17MB
05 - Pandas/020 Pandas - Text Methods for String Data.mp4
45.12MB
05 - Pandas/021 Pandas - Time Methods for Date and Time Data.mp4
80.19MB
05 - Pandas/022 Pandas Input and Output - CSV Files.mp4
37.15MB
05 - Pandas/023 Pandas Input and Output - HTML Tables.mp4
102.34MB
05 - Pandas/024 Pandas Input and Output - Excel Files.mp4
25.87MB
05 - Pandas/025 Pandas Input and Output - SQL Databases.mp4
95.98MB
05 - Pandas/026 Pandas Pivot Tables.mp4
129.09MB
05 - Pandas/027 Pandas Project Exercise Overview.mp4
39.43MB
05 - Pandas/028 Pandas Project Exercise Solutions.mp4
172.55MB
06 - Matplotlib/001 Introduction to Matplotlib.mp4
6.55MB
06 - Matplotlib/002 Matplotlib Basics.mp4
31.07MB
06 - Matplotlib/003 Matplotlib - Understanding the Figure Object.mp4
11.7MB
06 - Matplotlib/004 Matplotlib - Implementing Figures and Axes.mp4
34.86MB
06 - Matplotlib/005 Matplotlib - Figure Parameters.mp4
13.06MB
06 - Matplotlib/006 Matplotlib - Subplots Functionality.mp4
96.57MB
06 - Matplotlib/007 Matplotlib Styling - Legends.mp4
16.19MB
06 - Matplotlib/008 Matplotlib Styling - Colors and Styles.mp4
44.27MB
06 - Matplotlib/009 Advanced Matplotlib Commands (Optional).mp4
25.19MB
06 - Matplotlib/010 Matplotlib Exercise Questions Overview.mp4
48.99MB
06 - Matplotlib/011 Matplotlib Exercise Questions - Solutions.mp4
105.86MB
07 - Seaborn Data Visualizations/001 Introduction to Seaborn.mp4
5.74MB
07 - Seaborn Data Visualizations/002 Scatterplots with Seaborn.mp4
111.3MB
07 - Seaborn Data Visualizations/003 Distribution Plots - Part One - Understanding Plot Types.mp4
15.03MB
07 - Seaborn Data Visualizations/004 Distribution Plots - Part Two - Coding with Seaborn.mp4
59.21MB
07 - Seaborn Data Visualizations/005 Categorical Plots - Statistics within Categories - Understanding Plot Types.mp4
15.98MB
07 - Seaborn Data Visualizations/006 Categorical Plots - Statistics within Categories - Coding with Seaborn.mp4
51.65MB
07 - Seaborn Data Visualizations/007 Categorical Plots - Distributions within Categories - Understanding Plot Types.mp4
44.96MB
07 - Seaborn Data Visualizations/008 Categorical Plots - Distributions within Categories - Coding with Seaborn.mp4
84.57MB
07 - Seaborn Data Visualizations/009 Seaborn - Comparison Plots - Understanding the Plot Types.mp4
10.57MB
07 - Seaborn Data Visualizations/010 Seaborn - Comparison Plots - Coding with Seaborn.mp4
51.16MB
07 - Seaborn Data Visualizations/011 Seaborn Grid Plots.mp4
87.01MB
07 - Seaborn Data Visualizations/012 Seaborn - Matrix Plots.mp4
61.47MB
07 - Seaborn Data Visualizations/013 Seaborn Plot Exercises Overview.mp4
47.88MB
07 - Seaborn Data Visualizations/014 Seaborn Plot Exercises Solutions.mp4
105.72MB
08 - Data Analysis and Visualization Capstone Project Exercise/001 Capstone Project Overview.mp4
31.11MB
08 - Data Analysis and Visualization Capstone Project Exercise/002 Capstone Project Solutions - Part One.mp4
110.61MB
08 - Data Analysis and Visualization Capstone Project Exercise/003 Capstone Project Solutions - Part Two.mp4
106.18MB
08 - Data Analysis and Visualization Capstone Project Exercise/004 Capstone Project Solutions - Part Three.mp4
137.39MB
09 - Machine Learning Concepts Overview/001 Introduction to Machine Learning Overview Section.mp4
13.17MB
09 - Machine Learning Concepts Overview/002 Why Machine Learning_.mp4
21.04MB
09 - Machine Learning Concepts Overview/003 Types of Machine Learning Algorithms.mp4
18.08MB
09 - Machine Learning Concepts Overview/004 Supervised Machine Learning Process.mp4
33.53MB
09 - Machine Learning Concepts Overview/005 Companion Book - Introduction to Statistical Learning.mp4
5.11MB
10 - Linear Regression/001 Introduction to Linear Regression Section.mp4
2.58MB
10 - Linear Regression/002 Linear Regression - Algorithm History.mp4
54.82MB
10 - Linear Regression/003 Linear Regression - Understanding Ordinary Least Squares.mp4
86.37MB
10 - Linear Regression/004 Linear Regression - Cost Functions.mp4
16.63MB
10 - Linear Regression/005 Linear Regression - Gradient Descent.mp4
29.21MB
10 - Linear Regression/006 Python coding Simple Linear Regression.mp4
70.14MB
10 - Linear Regression/007 Overview of Scikit-Learn and Python.mp4
31.44MB
10 - Linear Regression/008 Linear Regression - Scikit-Learn Train Test Split.mp4
61.42MB
10 - Linear Regression/009 Linear Regression - Scikit-Learn Performance Evaluation - Regression.mp4
53.4MB
10 - Linear Regression/010 Linear Regression - Residual Plots.mp4
44.02MB
10 - Linear Regression/011 Linear Regression - Model Deployment and Coefficient Interpretation.mp4
81.14MB
10 - Linear Regression/012 Polynomial Regression - Theory and Motivation.mp4
22.25MB
10 - Linear Regression/013 Polynomial Regression - Creating Polynomial Features.mp4
40.09MB
10 - Linear Regression/014 Polynomial Regression - Training and Evaluation.mp4
36.3MB
10 - Linear Regression/015 Bias Variance Trade-Off.mp4
36.18MB
10 - Linear Regression/016 Polynomial Regression - Choosing Degree of Polynomial.mp4
55.68MB
10 - Linear Regression/017 Polynomial Regression - Model Deployment.mp4
23.22MB
10 - Linear Regression/018 Regularization Overview.mp4
15.52MB
10 - Linear Regression/019 Feature Scaling.mp4
24.34MB
10 - Linear Regression/020 Introduction to Cross Validation.mp4
32.97MB
10 - Linear Regression/021 Regularization Data Setup.mp4
20.16MB
10 - Linear Regression/022 L2 Regularization - Ridge Regression Theory.mp4
61.3MB
10 - Linear Regression/023 L2 Regularization - Ridge Regression - Python Implementation.mp4
89.37MB
10 - Linear Regression/024 L1 Regularization - Lasso Regression - Background and Implementation.mp4
94.65MB
10 - Linear Regression/025 L1 and L2 Regularization - Elastic Net.mp4
66.4MB
10 - Linear Regression/026 Linear Regression Project - Data Overview.mp4
16.94MB
11 - Feature Engineering and Data Preparation/002 Introduction to Feature Engineering and Data Preparation.mp4
36.11MB
11 - Feature Engineering and Data Preparation/003 Dealing with Outliers.mp4
103.32MB
11 - Feature Engineering and Data Preparation/004 Dealing with Missing Data _ Part One - Evaluation of Missing Data.mp4
19.05MB
11 - Feature Engineering and Data Preparation/005 Dealing with Missing Data _ Part Two - Filling or Dropping data based on Rows.mp4
117.56MB
11 - Feature Engineering and Data Preparation/006 Dealing with Missing Data _ Part 3 - Fixing data based on Columns.mp4
105.22MB
11 - Feature Engineering and Data Preparation/007 Dealing with Categorical Data - Encoding Options.mp4
58.87MB
12 - Cross Validation , Grid Search, and the Linear Regression Project/001 Section Overview and Introduction.mp4
5.61MB
12 - Cross Validation , Grid Search, and the Linear Regression Project/002 Cross Validation - Test _ Train Split.mp4
46.86MB
12 - Cross Validation , Grid Search, and the Linear Regression Project/003 Cross Validation - Test _ Validation _ Train Split.mp4
59.41MB
12 - Cross Validation , Grid Search, and the Linear Regression Project/004 Cross Validation - cross_val_score.mp4
44.46MB
12 - Cross Validation , Grid Search, and the Linear Regression Project/005 Cross Validation - cross_validate.mp4
45.01MB
12 - Cross Validation , Grid Search, and the Linear Regression Project/006 Grid Search.mp4
73.19MB
12 - Cross Validation , Grid Search, and the Linear Regression Project/007 Linear Regression Project Overview.mp4
23.63MB
12 - Cross Validation , Grid Search, and the Linear Regression Project/008 Linear Regression Project - Solutions.mp4
91.23MB
13 - Logistic Regression/002 Introduction to Logistic Regression Section.mp4
13.93MB
13 - Logistic Regression/003 Logistic Regression - Theory and Intuition - Part One_ The Logistic Function.mp4
17.31MB
13 - Logistic Regression/004 Logistic Regression - Theory and Intuition - Part Two_ Linear to Logistic.mp4
8.03MB
13 - Logistic Regression/005 Logistic Regression - Theory and Intuition - Linear to Logistic Math.mp4
36.04MB
13 - Logistic Regression/006 Logistic Regression - Theory and Intuition - Best fit with Maximum Likelihood.mp4
54.91MB
13 - Logistic Regression/007 Logistic Regression with Scikit-Learn - Part One - EDA.mp4
62.45MB
13 - Logistic Regression/008 Logistic Regression with Scikit-Learn - Part Two - Model Training.mp4
32.57MB
13 - Logistic Regression/009 Classification Metrics - Confusion Matrix and Accuracy.mp4
21.72MB
13 - Logistic Regression/010 Classification Metrics - Precison, Recall, F1-Score.mp4
33.14MB
13 - Logistic Regression/011 Classification Metrics - ROC Curves.mp4
16.07MB
13 - Logistic Regression/012 Logistic Regression with Scikit-Learn - Part Three - Performance Evaluation.mp4
57.03MB
13 - Logistic Regression/013 Multi-Class Classification with Logistic Regression - Part One - Data and EDA.mp4
37.38MB
13 - Logistic Regression/014 Multi-Class Classification with Logistic Regression - Part Two - Model.mp4
105.09MB
13 - Logistic Regression/015 Logistic Regression Exercise Project Overview.mp4
24.29MB
13 - Logistic Regression/016 Logistic Regression Project Exercise - Solutions.mp4
161.29MB
14 - KNN - K Nearest Neighbors/001 Introduction to KNN Section.mp4
3.65MB
14 - KNN - K Nearest Neighbors/002 KNN Classification - Theory and Intuition.mp4
23.55MB
14 - KNN - K Nearest Neighbors/003 KNN Coding with Python - Part One.mp4
61.55MB
14 - KNN - K Nearest Neighbors/004 KNN Coding with Python - Part Two - Choosing K.mp4
102.86MB
14 - KNN - K Nearest Neighbors/005 KNN Classification Project Exercise Overview.mp4
21.12MB
14 - KNN - K Nearest Neighbors/006 KNN Classification Project Exercise Solutions.mp4
105.03MB
15 - Support Vector Machines/001 Introduction to Support Vector Machines.mp4
2.79MB
15 - Support Vector Machines/002 History of Support Vector Machines.mp4
15.54MB
15 - Support Vector Machines/003 SVM - Theory and Intuition - Hyperplanes and Margins.mp4
47.74MB
15 - Support Vector Machines/004 SVM - Theory and Intuition - Kernel Intuition.mp4
9.83MB
15 - Support Vector Machines/005 SVM - Theory and Intuition - Kernel Trick and Mathematics.mp4
52.62MB
15 - Support Vector Machines/006 SVM with Scikit-Learn and Python - Classification Part One.mp4
46.28MB
15 - Support Vector Machines/007 SVM with Scikit-Learn and Python - Classification Part Two.mp4
90.63MB
15 - Support Vector Machines/008 SVM with Scikit-Learn and Python - Regression Tasks.mp4
76.27MB
15 - Support Vector Machines/009 Support Vector Machine Project Overview.mp4
34.84MB
15 - Support Vector Machines/010 Support Vector Machine Project Solutions.mp4
93.36MB
16 - Tree Based Methods_ Decision Tree Learning/001 Introduction to Tree Based Methods.mp4
2.33MB
16 - Tree Based Methods_ Decision Tree Learning/002 Decision Tree - History.mp4
35.58MB
16 - Tree Based Methods_ Decision Tree Learning/003 Decision Tree - Terminology.mp4
7.29MB
16 - Tree Based Methods_ Decision Tree Learning/004 Decision Tree - Understanding Gini Impurity.mp4
19.45MB
16 - Tree Based Methods_ Decision Tree Learning/005 Constructing Decision Trees with Gini Impurity - Part One.mp4
17.69MB
16 - Tree Based Methods_ Decision Tree Learning/006 Constructing Decision Trees with Gini Impurity - Part Two.mp4
52.35MB
16 - Tree Based Methods_ Decision Tree Learning/007 Coding Decision Trees - Part One - The Data.mp4
98.72MB
16 - Tree Based Methods_ Decision Tree Learning/008 Coding Decision Trees - Part Two -Creating the Model.mp4
115.8MB
17 - Random Forests/001 Introduction to Random Forests Section.mp4
2.87MB
17 - Random Forests/002 Random Forests - History and Motivation.mp4
24MB
17 - Random Forests/003 Random Forests - Key Hyperparameters.mp4
8.27MB
17 - Random Forests/004 Random Forests - Number of Estimators and Features in Subsets.mp4
27.31MB
17 - Random Forests/005 Random Forests - Bootstrapping and Out-of-Bag Error.mp4
32.72MB
17 - Random Forests/006 Coding Classification with Random Forest Classifier - Part One.mp4
52.1MB
17 - Random Forests/007 Coding Classification with Random Forest Classifier - Part Two.mp4
130.37MB
17 - Random Forests/008 Coding Regression with Random Forest Regressor - Part One - Data.mp4
13.68MB
17 - Random Forests/009 Coding Regression with Random Forest Regressor - Part Two - Basic Models.mp4
85.01MB
17 - Random Forests/010 Coding Regression with Random Forest Regressor - Part Three - Polynomials.mp4
45.54MB
17 - Random Forests/011 Coding Regression with Random Forest Regressor - Part Four - Advanced Models.mp4
50.67MB
18 - Boosting Methods/001 Introduction to Boosting Section.mp4
2.99MB
18 - Boosting Methods/002 Boosting Methods - Motivation and History.mp4
21.98MB
18 - Boosting Methods/003 AdaBoost Theory and Intuition.mp4
41.53MB
18 - Boosting Methods/004 AdaBoost Coding Part One - The Data.mp4
42.25MB
18 - Boosting Methods/005 AdaBoost Coding Part Two - The Model.mp4
63.11MB
18 - Boosting Methods/006 Gradient Boosting Theory.mp4
22.96MB
18 - Boosting Methods/007 Gradient Boosting Coding Walkthrough.mp4
57.91MB
19 - Supervised Learning Capstone Project/001 Introduction to Supervised Learning Capstone Project.mp4
29.84MB
19 - Supervised Learning Capstone Project/002 Solution Walkthrough - Supervised Learning Project - Data and EDA.mp4
106.1MB
19 - Supervised Learning Capstone Project/003 Solution Walkthrough - Supervised Learning Project - Cohort Analysis.mp4
130.14MB
19 - Supervised Learning Capstone Project/004 Solution Walkthrough - Supervised Learning Project - Tree Models.mp4
114.21MB
20 - Naive Bayes Classification and Natural Language Processing/001 Introduction to NLP and Naive Bayes Section.mp4
4.22MB
20 - Naive Bayes Classification and Natural Language Processing/002 Naive Bayes Algorithm - Part One - Bayes Theorem.mp4
22.04MB
20 - Naive Bayes Classification and Natural Language Processing/003 Naive Bayes Algorithm - Part Two - Model Algorithm.mp4
48.61MB
20 - Naive Bayes Classification and Natural Language Processing/004 Feature Extraction from Text - Part One - Theory and Intuition.mp4
29.4MB
20 - Naive Bayes Classification and Natural Language Processing/005 Feature Extraction from Text - Coding Count Vectorization Manually.mp4
62.89MB
20 - Naive Bayes Classification and Natural Language Processing/006 Feature Extraction from Text - Coding with Scikit-Learn.mp4
50.39MB
20 - Naive Bayes Classification and Natural Language Processing/007 Natural Language Processing - Classification of Text - Part One.mp4
28.26MB
20 - Naive Bayes Classification and Natural Language Processing/008 Natural Language Processing - Classification of Text - Part Two.mp4
34.77MB
20 - Naive Bayes Classification and Natural Language Processing/009 Text Classification Project Exercise Overview.mp4
30.54MB
20 - Naive Bayes Classification and Natural Language Processing/010 Text Classification Project Exercise Solutions.mp4
100.59MB
21 - Unsupervised Learning/001 Unsupervised Learning Overview.mp4
13.75MB
22 - K-Means Clustering/001 Introduction to K-Means Clustering Section.mp4
3.55MB
22 - K-Means Clustering/002 Clustering General Overview.mp4
24.86MB
22 - K-Means Clustering/003 K-Means Clustering Theory.mp4
52.49MB
22 - K-Means Clustering/004 K-Means Clustering - Coding Part One.mp4
97.9MB
22 - K-Means Clustering/005 K-Means Clustering Coding Part Two.mp4
80.85MB
22 - K-Means Clustering/006 K-Means Clustering Coding Part Three.mp4
59.77MB
22 - K-Means Clustering/007 K-Means Color Quantization - Part One.mp4
80.57MB
22 - K-Means Clustering/008 K-Means Color Quantization - Part Two.mp4
65.03MB
22 - K-Means Clustering/009 K-Means Clustering Exercise Overview.mp4
59.48MB
22 - K-Means Clustering/010 K-Means Clustering Exercise Solution - Part One.mp4
79.92MB
22 - K-Means Clustering/011 K-Means Clustering Exercise Solution - Part Two.mp4
108.19MB
22 - K-Means Clustering/012 K-Means Clustering Exercise Solution - Part Three.mp4
62.5MB
23 - Hierarchical Clustering/001 Introduction to Hierarchical Clustering.mp4
1.67MB
23 - Hierarchical Clustering/002 Hierarchical Clustering - Theory and Intuition.mp4
52.07MB
23 - Hierarchical Clustering/003 Hierarchical Clustering - Coding Part One - Data and Visualization.mp4
114.98MB
23 - Hierarchical Clustering/004 Hierarchical Clustering - Coding Part Two - Scikit-Learn.mp4
209.23MB
24 - DBSCAN - Density-based spatial clustering of applications with noise/001 Introduction to DBSCAN Section.mp4
1.8MB
24 - DBSCAN - Density-based spatial clustering of applications with noise/002 DBSCAN - Theory and Intuition.mp4
109.09MB
24 - DBSCAN - Density-based spatial clustering of applications with noise/003 DBSCAN versus K-Means Clustering.mp4
66.64MB
24 - DBSCAN - Density-based spatial clustering of applications with noise/004 DBSCAN - Hyperparameter Theory.mp4
13.86MB
24 - DBSCAN - Density-based spatial clustering of applications with noise/005 DBSCAN - Hyperparameter Tuning Methods.mp4
105.08MB
24 - DBSCAN - Density-based spatial clustering of applications with noise/006 DBSCAN - Outlier Project Exercise Overview.mp4
50.27MB
24 - DBSCAN - Density-based spatial clustering of applications with noise/007 DBSCAN - Outlier Project Exercise Solutions.mp4
127.93MB
25 - PCA - Principal Component Analysis and Manifold Learning/001 Introduction to Principal Component Analysis.mp4
5.08MB
25 - PCA - Principal Component Analysis and Manifold Learning/002 PCA Theory and Intuition - Part One.mp4
29.72MB
25 - PCA - Principal Component Analysis and Manifold Learning/003 PCA Theory and Intuition - Part Two.mp4
19.04MB
25 - PCA - Principal Component Analysis and Manifold Learning/004 PCA - Manual Implementation in Python.mp4
95.04MB
25 - PCA - Principal Component Analysis and Manifold Learning/005 PCA - SciKit-Learn.mp4
74.09MB
25 - PCA - Principal Component Analysis and Manifold Learning/006 PCA - Project Exercise Overview.mp4
52.77MB
25 - PCA - Principal Component Analysis and Manifold Learning/007 PCA - Project Exercise Solution.mp4
119.45MB
26 - Model Deployment/001 Model Deployment Section Overview.mp4
4.16MB
26 - Model Deployment/002 Model Deployment Considerations.mp4
18.31MB
26 - Model Deployment/003 Model Persistence.mp4
109.76MB
26 - Model Deployment/004 Model Deployment as an API - General Overview.mp4
17.48MB
26 - Model Deployment/006 Model API - Creating the Script.mp4
67.27MB
26 - Model Deployment/007 Testing the API.mp4
33.15MB
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