使用 Python A-Z 完成机器学习和数据科学
Complete Machine Learning and Data Science with Python A-Z
- 1. First Contact with Machine Learning
- 1. What is Machine Learning
- 2. Machine Learning Terminology
- 2. Installations for Python
- 1. Installing Anaconda Distribution for Windows
- 2. Installing Anaconda Distribution for MacOs
- 3. Installing Anaconda Distribution for Linux
- 4. Overview of Jupyter Notebook and Google Colab
- 3. Evaluation Metrics in Machine Learning
- 1. Classification vs Regression in Machine Learning
- 2. Machine Learning Model Performance Evaluation Classification Error Metrics
- 3. Evaluating Performance Regression Error Metrics in Python
- 4. Machine Learning With Python
- 4. Supervised Learning with Machine Learning
- 1. What is Supervised Learning in Machine Learning
- 5. Linear Regression Algorithm in Machine Learning A-Z
- 1. Linear Regression Algorithm Theory in Machine Learning A-Z
- 2. Linear Regression Algorithm With Python Part 1
- 3. Linear Regression Algorithm With Python Part 2
- 4. Linear Regression Algorithm with Python Part 3
- 5. Linear Regression Algorithm with Python Part 4
- 6. Bias Variance Trade-Off in Machine Learning
- 1. What is Bias Variance Trade-Off
- 7. Logistic Regression Algorithm in Machine Learning A-Z
- 1. What is Logistic Regression Algorithm in Machine Learning
- 2. Logistic Regression Algorithm with Python Part 1
- 3. Logistic Regression Algorithm with Python Part 2
- 4. Logistic Regression Algorithm with Python Part 3
- 5. Logistic Regression Algorithm with Python Part 4
- 6. Logistic Regression Algorithm with Python Part 5
- 8. K-fold Cross-Validation in Machine Learning A-Z
- 1. K-Fold Cross-Validation Theory
- 2. K-Fold Cross-Validation with Python
- 9. K Nearest Neighbors Algorithm in Machine Learning A-Z
- 1. K Nearest Neighbors Algorithm Theory
- 2. K Nearest Neighbors Algorithm with Python Part 1
- 3. K Nearest Neighbors Algorithm with Python Part 2
- 4. K Nearest Neighbors Algorithm with Python Part 3
- 10. Hyperparameter Optimization
- 1. Hyperparameter Optimization Theory
- 2. Hyperparameter Optimization with Python
- 11. Decision Tree Algorithm in Machine Learning A-Z
- 1. Decision Tree Algorithm Theory
- 2. Decision Tree Algorithm with Python Part 1
- 3. Decision Tree Algorithm with Python Part 2
- 4. Decision Tree Algorithm with Python Part 3
- 5. Decision Tree Algorithm with Python Part 4
- 6. Decision Tree Algorithm with Python Part 5
- 12. Random Forest Algorithm in Machine Learning A-Z
- 1. Random Forest Algorithm Theory
- 2. Random Forest Algorithm with Pyhon Part 1
- 3. Random Forest Algorithm with Pyhon Part 2
- 13. Support Vector Machine Algorithm in Machine Learning A-Z
- 1. Support Vector Machine Algorithm Theory
- 2. Support Vector Machine Algorithm with Python Part 1
- 3. Support Vector Machine Algorithm with Python Part 2
- 4. Support Vector Machine Algorithm with Python Part 3
- 5. Support Vector Machine Algorithm with Python Part 4
- 14. Unsupervised Learning with Machine Learning
- 1. Unsupervised Learning Overview
- 15. K Means Clustering Algorithm in Machine Learning A-Z
- 1. K Means Clustering Algorithm Theory
- 2. K Means Clustering Algorithm with Python Part 1
- 3. K Means Clustering Algorithm with Python Part 2
- 4. K Means Clustering Algorithm with Python Part 3
- 5. K Means Clustering Algorithm with Python Part 4
- 16. Hierarchical Clustering Algorithm in machine learning data science
- 1. Hierarchical Clustering Algorithm Theory
- 2. Hierarchical Clustering Algorithm with Python Part 1
- 3. Hierarchical Clustering Algorithm with Python Part 2
- 17. Principal Component Analysis (PCA) in Machine Learning A-Z
- 1. Principal Component Analysis (PCA) Theory
- 2. Principal Component Analysis (PCA) with Python Part 1
- 3. Principal Component Analysis (PCA) with Python Part 2
- 4. Principal Component Analysis (PCA) with Python Part 3
- 18. Recommender System Algorithm in Machine Learning A-Z
- 1. What is the Recommender System Part 1
- 2. What is the Recommender System Part 2