Download Python Machine Learning -all concepts a-z Torrent

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Python Machine Learning -all concepts a-z

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1 - Introduction to Machine Learning

1. Course Introduction.mp4

MP4

38.6 MB

10 - Feature Engineering

11 - Saving & Loading Models

12 - Practical ML Projects

13 - Deployment Basics

14 - Best Practices & ML Workflow

15 - Interview Preparation

2 - Python for Machine Learning

3 - ML Libraries in Python

10. ML Libraries in Python.mp4

MP4

10.6 MB

11. NumPy Basics.mp4

MP4

4.7 MB

12. Pandas Basics.mp4

MP4

3.8 MB

13. Scikit-Learn basics.mp4

MP4

3.5 MB

14. Matplotlib & Seaborn basics.mp4

MP4

3.4 MB

15. SciPy basics.mp4

MP4

2.7 MB

4 - Data Handling & Preprocessing

16. Loading & Inspecting Data.mp4

MP4

35.8 MB

17. Handling Missing Values & Feature Engineering.mp4

MP4

25.8 MB

18. Train-Test Split & Scaling Normalization.mp4

MP4

19.2 MB

5 - Exploratory Data Analysis (EDA)

19. Understanding Your Data.mp4

MP4

9.4 MB

20. Summary Statistics.mp4

MP4

10.7 MB

21. Data Visualisation Basics.mp4

MP4

19.3 MB

22. Scatter Plots & Bar Charts.mp4

MP4

13.4 MB

23. Correlation Analysis.mp4

MP4

19.1 MB

24. Distribution Plots.mp4

MP4

8.6 MB

6 - Supervised Learning - Regression

25. Understanding Regression Simple Linear Regression & Multiple Linear Regression.mp4

MP4

31.4 MB

26. Model Training & Evaluation.mp4

MP4

27.4 MB

27. MAE(Mean Absolute Error), MSE(Mean Squared Error), RMSE(Root Mean Squared Error).mp4

MP4

10.9 MB

7 - Supervised Learning - Classification

28. Logistic Regression.mp4

MP4

25.6 MB

29. K-Nearest Neighbors.mp4

MP4

36.6 MB

30. Decision Trees.mp4

MP4

15.7 MB

31. Random Forest.mp4

MP4

20 MB

32. Model Evaluation Metrics Accuracy, Precision, Recall, F1 Score.mp4

MP4

46.5 MB

8 - Model Evaluation & Validation

33. Confusion Matrix.mp4

MP4

55.3 MB

34. Cross-Validation.mp4

MP4

29.8 MB

35. Overfitting, Underfitting, Bias-Variance Tradeoff.mp4

MP4

23.6 MB

9 - Unsupervised Learning

36. K-Means Clustering.mp4	MP4	16.7 MB
37. Hierarchical Clustering.mp4	MP4	24.1 MB
38. Principal Component Analysis.mp4	MP4	26.6 MB

7. Why Python for ML.mp4

MP4

5.4 MB

8. Python ML Ecosystem.mp4

MP4

17.1 MB

9. Installation & Environment Setup with practical Demo.mp4

MP4

28.4 MB

61. Fundamental Concepts.mp4

MP4

7.7 MB

62. Algorithm Deep Dives.mp4

MP4

4.3 MB

63. Practical Scenarios & Coding Challenges.mp4

MP4

7.6 MB

64. Common Interview Topics & Final Tips.mp4

MP4

7.8 MB

55. Project Structure.mp4

MP4

6.5 MB

56. Ethical ML & Privacy.mp4

MP4

6.3 MB

57. Reproducibility.mp4

MP4

5.6 MB

58. Data Versioning.mp4

MP4

5 MB

59. Code Quality Standards.mp4

MP4

4.7 MB

60. Documentation Essentials.mp4

MP4

4.9 MB

49. What is Model Deployment.mp4

MP4

9.2 MB

50. Deployment Workflow 1. Save Trained Model.mp4

MP4

8.7 MB

51. Deployment Workflow 2. Create API Endpoint.mp4

MP4

1.4 MB

52. Deployment Workflow 3. Test Integration.mp4

MP4

5.4 MB

53. Deployment Workflow 4. Deploy to Production.mp4

MP4

4.8 MB

54. Introduction to FastAPI for ML.mp4

MP4

2 MB

48. Practical ML Project- Live Example.mp4

MP4

35.7 MB

43. Model Persistence.mp4

MP4

19.9 MB

44. Training Phase.mp4

MP4

19.6 MB

45. Saving with Pickle.mp4

MP4

10.2 MB

46. Using Joblib.mp4

MP4

8 MB

47. Loading for Prediction.mp4

MP4

28.3 MB

39. Encoding Categorical Variables.mp4

MP4

21.6 MB

40. Handling Outliers.mp4

MP4

16.5 MB

41. Feature Scaling.mp4

MP4

26.2 MB

42. Creating New Features.mp4

MP4

20.9 MB

2. What is Machine Learning.mp4

MP4

7 MB

3. ML vs Traditional Programming.mp4

MP4

5.1 MB

4. Supervised Learning.mp4

MP4

4.1 MB

5. Unsupervised Learning.mp4

MP4

3.5 MB

6. Reinforcement Learning.mp4

MP4

4 MB

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Python Machine Learning -all concepts a-z

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