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[FreeCourseSite.com] Udemy - Python for Data Science & Machine Learning from A-Z
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2022-7-16 09:00
2024-9-2 02:26
186
7.32 GB
140
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Udemy
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Python
for
Data
Science
&
Machine
Learning
from
A-Z
文件列表
1. Introduction/1. Who is This Course For.mp4
17.16MB
1. Introduction/2. Data Science + Machine Learning Marketplace.mp4
46.94MB
1. Introduction/3. Data Science Job Opportunities.mp4
29.42MB
1. Introduction/4. Data Science Job Roles.mp4
79.8MB
1. Introduction/5. What is a Data Scientist.mp4
127.47MB
1. Introduction/6. How To Get a Data Science Job.mp4
131.19MB
1. Introduction/7. Data Science Projects Overview.mp4
79.48MB
10. Data Loading & Exploration/1. Exploratory Data Analysis.mp4
50.56MB
11. Data Cleaning/1. Feature Scaling.mp4
19.38MB
11. Data Cleaning/2. Data Cleaning.mp4
30.21MB
12. Feature Selecting and Engineering/1. Feature Engineering.mp4
18.41MB
13. Linear and Logistic Regression/1. Linear Regression Intro.mp4
30.8MB
13. Linear and Logistic Regression/2. Gradient Descent.mp4
15.93MB
13. Linear and Logistic Regression/3. Linear Regression + Correlation Methods.mp4
110.38MB
13. Linear and Logistic Regression/4. Linear Regression Implementation.mp4
17.86MB
13. Linear and Logistic Regression/5. Logistic Regression.mp4
8.9MB
14. K Nearest Neighbors/1. KNN Overview.mp4
12.89MB
14. K Nearest Neighbors/10. Feature scaling in KNN.mp4
49.39MB
14. K Nearest Neighbors/11. Curse of dimensionality.mp4
45.99MB
14. K Nearest Neighbors/12. KNN use cases.mp4
28.92MB
14. K Nearest Neighbors/13. KNN pros and cons.mp4
30.45MB
14. K Nearest Neighbors/2. parametric vs non-parametric models.mp4
15.63MB
14. K Nearest Neighbors/3. EDA on Iris Dataset.mp4
161.88MB
14. K Nearest Neighbors/4. The KNN Intuition.mp4
8.09MB
14. K Nearest Neighbors/5. Implement the KNN algorithm from scratch.mp4
86.97MB
14. K Nearest Neighbors/6. Compare the result with the sklearn library.mp4
24.57MB
14. K Nearest Neighbors/7. Hyperparameter tuning using the cross-validation.mp4
90.3MB
14. K Nearest Neighbors/8. The decision boundary visualization.mp4
16.94MB
14. K Nearest Neighbors/9. Manhattan vs Euclidean Distance.mp4
30.49MB
15. Decision Trees/1. Decision Trees Section Overview.mp4
16.46MB
15. Decision Trees/10. Visualizing the tree.mp4
68.17MB
15. Decision Trees/11. Plot the features importance.mp4
31.67MB
15. Decision Trees/12. Decision Trees Hyper-parameters.mp4
81.27MB
15. Decision Trees/13. Pruning.mp4
112.97MB
15. Decision Trees/14. [Optional] Gain Ration.mp4
19.18MB
15. Decision Trees/15. Decision Trees Pros and Cons.mp4
47.74MB
15. Decision Trees/16. [Project] Predict whether income exceeds $50Kyr - Overview.mp4
15.11MB
15. Decision Trees/2. EDA on Adult Dataset.mp4
123.19MB
15. Decision Trees/3. What is Entropy and Information Gain.mp4
136.08MB
15. Decision Trees/4. The Decision Tree ID3 algorithm from scratch Part 1.mp4
85.27MB
15. Decision Trees/5. The Decision Tree ID3 algorithm from scratch Part 2.mp4
63.96MB
15. Decision Trees/6. The Decision Tree ID3 algorithm from scratch Part 3.mp4
33.41MB
15. Decision Trees/7. ID3 - Putting Everything Together.mp4
182.48MB
15. Decision Trees/8. Evaluating our ID3 implementation.mp4
121.94MB
15. Decision Trees/9. Compare with Sklearn implementation.mp4
65.58MB
16. Ensemble Learning and Random Forests/1. Ensemble Learning Section Overview.mp4
16.07MB
16. Ensemble Learning and Random Forests/10. Random Forests Pros and Cons.mp4
19.69MB
16. Ensemble Learning and Random Forests/11. What is Boosting.mp4
35.44MB
16. Ensemble Learning and Random Forests/12. AdaBoost Part 1.mp4
25.53MB
16. Ensemble Learning and Random Forests/13. AdaBoost Part 2.mp4
85.94MB
16. Ensemble Learning and Random Forests/2. What is Ensemble Learning.mp4
91.97MB
16. Ensemble Learning and Random Forests/3. What is Bootstrap Sampling.mp4
55.88MB
16. Ensemble Learning and Random Forests/4. What is Bagging.mp4
29.48MB
16. Ensemble Learning and Random Forests/5. Out-of-Bag Error (OOB Error).mp4
42.03MB
16. Ensemble Learning and Random Forests/6. Implementing Random Forests from scratch Part 1.mp4
202.55MB
16. Ensemble Learning and Random Forests/7. Implementing Random Forests from scratch Part 2.mp4
50.5MB
16. Ensemble Learning and Random Forests/8. Compare with sklearn implementation.mp4
27.65MB
16. Ensemble Learning and Random Forests/9. Random Forests Hyper-Parameters.mp4
39.67MB
17. Support Vector Machines/1. SVM Outline.mp4
35.31MB
17. Support Vector Machines/10. SMV - Project Overview.mp4
39.61MB
17. Support Vector Machines/2. SVM intuition.mp4
48.86MB
17. Support Vector Machines/3. Hard vs Soft Margins.mp4
65.64MB
17. Support Vector Machines/4. C hyper-parameter.mp4
21.06MB
17. Support Vector Machines/5. Kernel Trick.mp4
77.05MB
17. Support Vector Machines/6. SVM - Kernel Types.mp4
126.38MB
17. Support Vector Machines/7. SVM with Linear Dataset (Iris).mp4
101.56MB
17. Support Vector Machines/8. SVM with Non-linear Dataset.mp4
111.55MB
17. Support Vector Machines/9. SVM with Regression.mp4
25MB
18. K-means/1. Unsupervised Machine Learning Intro.mp4
100.92MB
18. K-means/2. Unsupervised Machine Learning Continued.mp4
83.13MB
18. K-means/3. Representing Clusters.mp4
109.62MB
19. PCA/1. PCA Section Overview.mp4
31.77MB
19. PCA/10. PCA - Feature Scaling and Screen Plot.mp4
68.2MB
19. PCA/11. PCA - Supervised vs Unsupervised.mp4
35.79MB
19. PCA/12. PCA - Visualization.mp4
68.02MB
19. PCA/2. What is PCA.mp4
47.26MB
19. PCA/3. PCA Drawbacks.mp4
19.44MB
19. PCA/4. PCA Algorithm Steps (Mathematics).mp4
57.73MB
19. PCA/5. Covariance Matrix vs SVD.mp4
38.74MB
19. PCA/6. PCA - Main Applications.mp4
10.05MB
19. PCA/7. PCA - Image Compression.mp4
249.92MB
19. PCA/8. PCA Data Preprocessing.mp4
120.46MB
19. PCA/9. PCA - Biplot and the Screen Plot.mp4
135.6MB
2. Data Science & Machine Learning Concepts/1. Why We Use Python.mp4
13.51MB
2. Data Science & Machine Learning Concepts/2. What is Data Science.mp4
87.99MB
2. Data Science & Machine Learning Concepts/3. What is Machine Learning.mp4
83.41MB
2. Data Science & Machine Learning Concepts/4. Machine Learning Concepts & Algorithms.mp4
77.98MB
2. Data Science & Machine Learning Concepts/5. What is Deep Learning.mp4
77.81MB
2. Data Science & Machine Learning Concepts/6. Machine Learning vs Deep Learning.mp4
75.92MB
20. Data Science Career/1. Creating A Data Science Resume.mp4
37.08MB
20. Data Science Career/2. Data Science Cover Letter.mp4
22.96MB
20. Data Science Career/3. How to Contact Recruiters.mp4
24.65MB
20. Data Science Career/4. Getting Started with Freelancing.mp4
30.24MB
20. Data Science Career/5. Top Freelance Websites.mp4
29.55MB
20. Data Science Career/6. Personal Branding.mp4
30.49MB
20. Data Science Career/7. Networking Do's and Don'ts.mp4
23.7MB
20. Data Science Career/8. Importance of a Website.mp4
15.37MB
3. Python For Data Science/1. What is Programming.mp4
18.35MB
3. Python For Data Science/10. Python Conditional Statements.mp4
54.61MB
3. Python For Data Science/11. Python For Loops and While Loops.mp4
25.61MB
3. Python For Data Science/12. Python Lists.mp4
21.44MB
3. Python For Data Science/13. More about Lists.mp4
60.42MB
3. Python For Data Science/14. Python Tuples.mp4
54.53MB
3. Python For Data Science/15. Python Dictionaries.mp4
104.18MB
3. Python For Data Science/16. Python Sets.mp4
29.43MB
3. Python For Data Science/17. Compound Data Types & When to use each one.mp4
47.07MB
3. Python For Data Science/18. Python Functions.mp4
62.51MB
3. Python For Data Science/19. Object Oriented Programming in Python.mp4
70.25MB
3. Python For Data Science/2. Why Python for Data Science.mp4
16.32MB
3. Python For Data Science/3. What is Jupyter.mp4
14.57MB
3. Python For Data Science/4. What is Google Colab.mp4
8.26MB
3. Python For Data Science/5. Python Variables, Booleans and None.mp4
38.26MB
3. Python For Data Science/6. Getting Started with Google Colab.mp4
35.09MB
3. Python For Data Science/7. Python Operators.mp4
86.76MB
3. Python For Data Science/8. Python Numbers & Booleans.mp4
25.61MB
3. Python For Data Science/9. Python Strings.mp4
56.27MB
4. Statistics for Data Science/1. Intro To Statistics.mp4
21.24MB
4. Statistics for Data Science/2. Descriptive Statistics.mp4
21.48MB
4. Statistics for Data Science/3. Measure of Variability.mp4
38.2MB
4. Statistics for Data Science/4. Measure of Variability Continued.mp4
34.61MB
4. Statistics for Data Science/5. Measures of Variable Relationship.mp4
23.57MB
4. Statistics for Data Science/6. Inferential Statistics.mp4
45.01MB
4. Statistics for Data Science/7. Measure of Asymmetry.mp4
6.76MB
4. Statistics for Data Science/8. Sampling Distribution.mp4
26.46MB
5. Probability & Hypothesis Testing/1. What is Exactly is Probability.mp4
27.17MB
5. Probability & Hypothesis Testing/2. Expected Values.mp4
14.72MB
5. Probability & Hypothesis Testing/3. Relative Frequency.mp4
32.69MB
5. Probability & Hypothesis Testing/4. Hypothesis Testing Overview.mp4
60.59MB
6. NumPy Data Analysis/1. Intro NumPy Array Data Types.mp4
34.67MB
6. NumPy Data Analysis/2. NumPy Arrays.mp4
32.33MB
6. NumPy Data Analysis/3. NumPy Arrays Basics.mp4
39.98MB
6. NumPy Data Analysis/4. NumPy Array Indexing.mp4
34.74MB
6. NumPy Data Analysis/5. NumPy Array Computations.mp4
16.96MB
6. NumPy Data Analysis/6. Broadcasting.mp4
17.86MB
7. Pandas Data Analysis/1. Introduction to Pandas.mp4
46.83MB
7. Pandas Data Analysis/2. Introduction to Pandas Continued.mp4
71.1MB
8. Python Data Visualization/1. Data Visualization Overview.mp4
73.08MB
8. Python Data Visualization/2. Different Data Visualization Libraries in Python.mp4
15.95MB
8. Python Data Visualization/3. Python Data Visualization Implementation.mp4
27.43MB
9. Machine Learning/1. Introduction To Machine Learning.mp4
98.71MB
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