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[Udemy] Python for Data Science & Machine Learning from A-Z (01.2021)
magnet:?xt=urn:btih:754bac83d978e5020ae6325bd70ca23598c68796&dn=[Udemy] Python for Data Science & Machine Learning from A-Z (01.2021)
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文件列表详情
754bac83d978e5020ae6325bd70ca23598c68796
infohash:
140
文件数量
7.32 GB
文件大小
2022-8-17 16:52
创建日期
2024-10-1 16:58
最后访问
相关分词
Udemy
Python
for
Data
Science
&
Machine
Learning
from
A-Z
01
2021
1. Introduction/1. Who is This Course For.mp4 17.16 MB
1. Introduction/2. Data Science + Machine Learning Marketplace.mp4 46.94 MB
1. Introduction/3. Data Science Job Opportunities.mp4 29.42 MB
1. Introduction/4. Data Science Job Roles.mp4 79.8 MB
1. Introduction/5. What is a Data Scientist.mp4 127.47 MB
1. Introduction/6. How To Get a Data Science Job.mp4 131.19 MB
1. Introduction/7. Data Science Projects Overview.mp4 79.48 MB
10. Data Loading & Exploration/1. Exploratory Data Analysis.mp4 50.56 MB
11. Data Cleaning/1. Feature Scaling.mp4 19.38 MB
11. Data Cleaning/2. Data Cleaning.mp4 30.21 MB
12. Feature Selecting and Engineering/1. Feature Engineering.mp4 18.41 MB
13. Linear and Logistic Regression/1. Linear Regression Intro.mp4 30.8 MB
13. Linear and Logistic Regression/2. Gradient Descent.mp4 15.93 MB
13. Linear and Logistic Regression/3. Linear Regression + Correlation Methods.mp4 110.38 MB
13. Linear and Logistic Regression/4. Linear Regression Implementation.mp4 17.86 MB
13. Linear and Logistic Regression/5. Logistic Regression.mp4 8.9 MB
14. K Nearest Neighbors/1. KNN Overview.mp4 12.89 MB
14. K Nearest Neighbors/10. Feature scaling in KNN.mp4 49.39 MB
14. K Nearest Neighbors/11. Curse of dimensionality.mp4 45.99 MB
14. K Nearest Neighbors/12. KNN use cases.mp4 28.92 MB
14. K Nearest Neighbors/13. KNN pros and cons.mp4 30.45 MB
14. K Nearest Neighbors/2. parametric vs non-parametric models.mp4 15.63 MB
14. K Nearest Neighbors/3. EDA on Iris Dataset.mp4 161.88 MB
14. K Nearest Neighbors/4. The KNN Intuition.mp4 8.09 MB
14. K Nearest Neighbors/5. Implement the KNN algorithm from scratch.mp4 86.97 MB
14. K Nearest Neighbors/6. Compare the result with the sklearn library.mp4 24.57 MB
14. K Nearest Neighbors/7. Hyperparameter tuning using the cross-validation.mp4 90.3 MB
14. K Nearest Neighbors/8. The decision boundary visualization.mp4 16.94 MB
14. K Nearest Neighbors/9. Manhattan vs Euclidean Distance.mp4 30.49 MB
15. Decision Trees/1. Decision Trees Section Overview.mp4 16.46 MB
15. Decision Trees/10. Visualizing the tree.mp4 68.17 MB
15. Decision Trees/11. Plot the features importance.mp4 31.67 MB
15. Decision Trees/12. Decision Trees Hyper-parameters.mp4 81.27 MB
15. Decision Trees/13. Pruning.mp4 112.97 MB
15. Decision Trees/14. [Optional] Gain Ration.mp4 19.18 MB
15. Decision Trees/15. Decision Trees Pros and Cons.mp4 47.74 MB
15. Decision Trees/16. [Project] Predict whether income exceeds $50Kyr - Overview.mp4 15.11 MB
15. Decision Trees/2. EDA on Adult Dataset.mp4 123.19 MB
15. Decision Trees/3. What is Entropy and Information Gain.mp4 136.08 MB
15. Decision Trees/4. The Decision Tree ID3 algorithm from scratch Part 1.mp4 85.27 MB
15. Decision Trees/5. The Decision Tree ID3 algorithm from scratch Part 2.mp4 63.96 MB
15. Decision Trees/6. The Decision Tree ID3 algorithm from scratch Part 3.mp4 33.41 MB
15. Decision Trees/7. ID3 - Putting Everything Together.mp4 182.48 MB
15. Decision Trees/8. Evaluating our ID3 implementation.mp4 121.94 MB
15. Decision Trees/9. Compare with Sklearn implementation.mp4 65.58 MB
16. Ensemble Learning and Random Forests/1. Ensemble Learning Section Overview.mp4 16.07 MB
16. Ensemble Learning and Random Forests/10. Random Forests Pros and Cons.mp4 19.69 MB
16. Ensemble Learning and Random Forests/11. What is Boosting.mp4 35.44 MB
16. Ensemble Learning and Random Forests/12. AdaBoost Part 1.mp4 25.53 MB
16. Ensemble Learning and Random Forests/13. AdaBoost Part 2.mp4 85.94 MB
16. Ensemble Learning and Random Forests/2. What is Ensemble Learning.mp4 91.97 MB
16. Ensemble Learning and Random Forests/3. What is Bootstrap Sampling.mp4 55.88 MB
16. Ensemble Learning and Random Forests/4. What is Bagging.mp4 29.48 MB
16. Ensemble Learning and Random Forests/5. Out-of-Bag Error (OOB Error).mp4 42.03 MB
16. Ensemble Learning and Random Forests/6. Implementing Random Forests from scratch Part 1.mp4 202.55 MB
16. Ensemble Learning and Random Forests/7. Implementing Random Forests from scratch Part 2.mp4 50.5 MB
16. Ensemble Learning and Random Forests/8. Compare with sklearn implementation.mp4 27.65 MB
16. Ensemble Learning and Random Forests/9. Random Forests Hyper-Parameters.mp4 39.67 MB
17. Support Vector Machines/1. SVM Outline.mp4 35.31 MB
17. Support Vector Machines/10. SMV - Project Overview.mp4 39.61 MB
17. Support Vector Machines/2. SVM intuition.mp4 48.86 MB
17. Support Vector Machines/3. Hard vs Soft Margins.mp4 65.64 MB
17. Support Vector Machines/4. C hyper-parameter.mp4 21.06 MB
17. Support Vector Machines/5. Kernel Trick.mp4 77.05 MB
17. Support Vector Machines/6. SVM - Kernel Types.mp4 126.38 MB
17. Support Vector Machines/7. SVM with Linear Dataset (Iris).mp4 101.56 MB
17. Support Vector Machines/8. SVM with Non-linear Dataset.mp4 111.55 MB
17. Support Vector Machines/9. SVM with Regression.mp4 25 MB
18. K-means/1. Unsupervised Machine Learning Intro.mp4 100.92 MB
18. K-means/2. Unsupervised Machine Learning Continued.mp4 83.13 MB
18. K-means/3. Representing Clusters.mp4 109.62 MB
19. PCA/1. PCA Section Overview.mp4 31.77 MB
19. PCA/10. PCA - Feature Scaling and Screen Plot.mp4 68.2 MB
19. PCA/11. PCA - Supervised vs Unsupervised.mp4 35.79 MB
19. PCA/12. PCA - Visualization.mp4 68.02 MB
19. PCA/2. What is PCA.mp4 47.26 MB
19. PCA/3. PCA Drawbacks.mp4 19.44 MB
19. PCA/4. PCA Algorithm Steps (Mathematics).mp4 57.73 MB
19. PCA/5. Covariance Matrix vs SVD.mp4 38.74 MB
19. PCA/6. PCA - Main Applications.mp4 10.05 MB
19. PCA/7. PCA - Image Compression.mp4 249.92 MB
19. PCA/8. PCA Data Preprocessing.mp4 120.46 MB
19. PCA/9. PCA - Biplot and the Screen Plot.mp4 135.6 MB
2. Data Science & Machine Learning Concepts/1. Why We Use Python.mp4 13.51 MB
2. Data Science & Machine Learning Concepts/2. What is Data Science.mp4 87.99 MB
2. Data Science & Machine Learning Concepts/3. What is Machine Learning.mp4 83.41 MB
2. Data Science & Machine Learning Concepts/4. Machine Learning Concepts & Algorithms.mp4 77.98 MB
2. Data Science & Machine Learning Concepts/5. What is Deep Learning.mp4 77.81 MB
2. Data Science & Machine Learning Concepts/6. Machine Learning vs Deep Learning.mp4 75.92 MB
20. Data Science Career/1. Creating A Data Science Resume.mp4 37.08 MB
20. Data Science Career/2. Data Science Cover Letter.mp4 22.96 MB
20. Data Science Career/3. How to Contact Recruiters.mp4 24.65 MB
20. Data Science Career/4. Getting Started with Freelancing.mp4 30.24 MB
20. Data Science Career/5. Top Freelance Websites.mp4 29.55 MB
20. Data Science Career/6. Personal Branding.mp4 30.49 MB
20. Data Science Career/7. Networking Do's and Don'ts.mp4 23.7 MB
20. Data Science Career/8. Importance of a Website.mp4 15.37 MB
3. Python For Data Science/1. What is Programming.mp4 18.35 MB
3. Python For Data Science/10. Python Conditional Statements.mp4 54.61 MB
3. Python For Data Science/11. Python For Loops and While Loops.mp4 25.61 MB
3. Python For Data Science/12. Python Lists.mp4 21.44 MB
3. Python For Data Science/13. More about Lists.mp4 60.42 MB
3. Python For Data Science/14. Python Tuples.mp4 54.53 MB
3. Python For Data Science/15. Python Dictionaries.mp4 104.18 MB
3. Python For Data Science/16. Python Sets.mp4 29.43 MB
3. Python For Data Science/17. Compound Data Types & When to use each one.mp4 47.07 MB
3. Python For Data Science/18. Python Functions.mp4 62.51 MB
3. Python For Data Science/19. Object Oriented Programming in Python.mp4 70.25 MB
3. Python For Data Science/2. Why Python for Data Science.mp4 16.32 MB
3. Python For Data Science/3. What is Jupyter.mp4 14.57 MB
3. Python For Data Science/4. What is Google Colab.mp4 8.26 MB
3. Python For Data Science/5. Python Variables, Booleans and None.mp4 38.26 MB
3. Python For Data Science/6. Getting Started with Google Colab.mp4 35.09 MB
3. Python For Data Science/7. Python Operators.mp4 86.76 MB
3. Python For Data Science/8. Python Numbers & Booleans.mp4 25.61 MB
3. Python For Data Science/9. Python Strings.mp4 56.27 MB
4. Statistics for Data Science/1. Intro To Statistics.mp4 21.24 MB
4. Statistics for Data Science/2. Descriptive Statistics.mp4 21.48 MB
4. Statistics for Data Science/3. Measure of Variability.mp4 38.2 MB
4. Statistics for Data Science/4. Measure of Variability Continued.mp4 34.61 MB
4. Statistics for Data Science/5. Measures of Variable Relationship.mp4 23.57 MB
4. Statistics for Data Science/6. Inferential Statistics.mp4 45.01 MB
4. Statistics for Data Science/7. Measure of Asymmetry.mp4 6.76 MB
4. Statistics for Data Science/8. Sampling Distribution.mp4 26.46 MB
5. Probability & Hypothesis Testing/1. What is Exactly is Probability.mp4 27.17 MB
5. Probability & Hypothesis Testing/2. Expected Values.mp4 14.72 MB
5. Probability & Hypothesis Testing/3. Relative Frequency.mp4 32.69 MB
5. Probability & Hypothesis Testing/4. Hypothesis Testing Overview.mp4 60.59 MB
6. NumPy Data Analysis/1. Intro NumPy Array Data Types.mp4 34.67 MB
6. NumPy Data Analysis/2. NumPy Arrays.mp4 32.33 MB
6. NumPy Data Analysis/3. NumPy Arrays Basics.mp4 39.98 MB
6. NumPy Data Analysis/4. NumPy Array Indexing.mp4 34.74 MB
6. NumPy Data Analysis/5. NumPy Array Computations.mp4 16.96 MB
6. NumPy Data Analysis/6. Broadcasting.mp4 17.86 MB
7. Pandas Data Analysis/1. Introduction to Pandas.mp4 46.83 MB
7. Pandas Data Analysis/2. Introduction to Pandas Continued.mp4 71.1 MB
8. Python Data Visualization/1. Data Visualization Overview.mp4 73.08 MB
8. Python Data Visualization/2. Different Data Visualization Libraries in Python.mp4 15.95 MB
8. Python Data Visualization/3. Python Data Visualization Implementation.mp4 27.43 MB
9. Machine Learning/1. Introduction To Machine Learning.mp4 98.71 MB
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