Complete Data Science & Machine Learning A-Z with Python
Isi Folder / Files :
1. Installations
10. Element Selection Operations in DataFrame Structures
11. Structural Operations on Pandas DataFrame
12. Multi-Indexed DataFrame Structures
13. Structural Concatenation Operations in Pandas DataFrame
14. Functions That Can Be Applied on a DataFrame
15. Pivot Tables in Pandas Library
16. File Operations in Pandas Library
17. Code Files And Resources Python data analysis and visualization
18. Introduction to Data Visualization with Python
19. Fundamentals of Python 3
2. NumPy Library Introduction
20. Object Oriented Programming (OOP)
21. Matplotlib
22. Seaborn
23. Geoplotlib
24. First Contact with Machine Learning
25. Evaluation Metrics in Machine Learning
26. Supervised Learning with Machine Learning
27. Linear Regression Algorithm in Machine Learning A-Z
28. Bias Variance Trade-Off in Machine Learning
29. Logistic Regression Algorithm in Machine Learning A-Z
3. Creating NumPy Array in Python
30. K-fold Cross-Validation in Machine Learning A-Z
31. K Nearest Neighbors Algorithm in Machine Learning A-Z
32. Hyperparameter Optimization
33. Decision Tree Algorithm in Machine Learning A-Z
34. Random Forest Algorithm in Machine Learning A-Z
35. Support Vector Machine Algorithm in Machine Learning A-Z
36. Unsupervised Learning with Machine Learning
37. K Means Clustering Algorithm in Machine Learning A-Z
38. Hierarchical Clustering Algorithm in machine learning data science
39. Principal Component Analysis (PCA) in Machine Learning A-Z
4. Functions in the NumPy Library
40. Recommender System Algorithm in Machine Learning A-Z
41. First Contact with Kaggle
42. Competition Section on Kaggle
43. Dataset Section on Kaggle
44. Code Section on Kaggle
45. Discussion Section on Kaggle
46. Other Most Used Options on Kaggle
47. Details on Kaggle
48. Introduction to Machine Learning with Real Hearth Attack Prediction Project
49. First Organization
5. Indexing, Slicing, and Assigning NumPy Arrays
50. Preparation For Exploratory Data Analysis (EDA) in Data Science
51. Exploratory Data Analysis (EDA) - Uni-variate Analysis
52. Exploratory Data Analysis (EDA) - Bi-variate Analysis
53. Preparation for Modelling in Machine Learning
54. Modelling for Machine Learning
55. Conclusion
56. Extra
6. Operations in Numpy Library
7. Pandas Library Introduction
8. Series Structures in the Pandas Library
9. DataFrame Structures in Pandas Library
Keywords : No