FreeCourseLab com Udemy - Machine Learning & Data Science A-Z Hands-on Python 2021

1. 01 Introduction/001 Course Content.mp417.07MB
2. 01 Introduction/002 What is Machine Learning_ Some Basic Terms.mp425.82MB
3. 01 Introduction/004 Python IDE.mp47.51MB
4. 01 Introduction/005 IDE Installation.mp422.28MB
5. 01 Introduction/006 Installation of Required Libraries.mp470.78MB
6. 01 Introduction/007 Spyder Interface.mp446.36MB
7. 02 Machine Learning Useful Packages (Libraries)/002 NumPy1.mp437.49MB
8. 02 Machine Learning Useful Packages (Libraries)/003 NumPy2.mp456.91MB
9. 02 Machine Learning Useful Packages (Libraries)/004 NumPy3.mp484.52MB
10. 02 Machine Learning Useful Packages (Libraries)/005 NumPy4.mp456.56MB
11. 02 Machine Learning Useful Packages (Libraries)/006 NumPy5.mp4152.64MB
12. 02 Machine Learning Useful Packages (Libraries)/007 NumPy6.mp4134.5MB
13. 02 Machine Learning Useful Packages (Libraries)/008 Pandas1.mp495.61MB
14. 02 Machine Learning Useful Packages (Libraries)/009 Pandas2.mp4116.94MB
15. 02 Machine Learning Useful Packages (Libraries)/010 Pandas3.mp4117.83MB
16. 02 Machine Learning Useful Packages (Libraries)/011 Pandas4.mp4203.04MB
17. 02 Machine Learning Useful Packages (Libraries)/012 Visualization with Matplotlib1.mp499.45MB
18. 02 Machine Learning Useful Packages (Libraries)/013 Visualization with Matplotlib2.mp4205.24MB
19. 02 Machine Learning Useful Packages (Libraries)/014 Visualization with Matplotlib3.mp4188.84MB
20. 02 Machine Learning Useful Packages (Libraries)/015 Visualization with Matplotlib4.mp4142.99MB
21. 02 Machine Learning Useful Packages (Libraries)/016 Visualization with Matplotlib5.mp4129.25MB
22. 03 Data Preprocessing/001 Reading and Modifying a Dataset.mp4154.55MB
23. 03 Data Preprocessing/002 Statistics1.mp434.04MB
24. 03 Data Preprocessing/003 Statistics2.mp4207.49MB
25. 03 Data Preprocessing/004 Statistics3 - Covariance.mp4107.48MB
26. 03 Data Preprocessing/005 Missing Values1.mp4129.64MB
27. 03 Data Preprocessing/006 Missing Values2.mp4219.38MB
28. 03 Data Preprocessing/007 Outlier Detection1.mp473.2MB
29. 03 Data Preprocessing/008 Outlier Detection2.mp4130.66MB
30. 03 Data Preprocessing/009 Outlier Detection3.mp431.01MB
31. 03 Data Preprocessing/010 Concatenation.mp465.88MB
32. 03 Data Preprocessing/011 Dummy Variable.mp457.59MB
33. 03 Data Preprocessing/012 Normalization.mp4186.87MB
34. 04 Machine Learning Introduction/001 Learning Types.mp445.44MB
35. 05 Supervised Learning - Classification/001 Supervised Learning Models - Introduction and Understanding the Data.mp4233.75MB
36. 05 Supervised Learning - Classification/002 k-NN Concepts.mp448.03MB
37. 05 Supervised Learning - Classification/003 k-NN Model Development.mp4140.65MB
38. 05 Supervised Learning - Classification/004 k-NN Training-Set and Test-Set Creation.mp4228.42MB
39. 05 Supervised Learning - Classification/005 Decision Tree Concepts.mp425.62MB
40. 05 Supervised Learning - Classification/006 Decision Tree Model Development.mp466.84MB
41. 05 Supervised Learning - Classification/007 Decision Tree - Cross Validation.mp454.64MB
42. 05 Supervised Learning - Classification/008 Naive Bayes Concepts.mp459.23MB
43. 05 Supervised Learning - Classification/009 Naive Bayes Model Development.mp458.95MB
44. 05 Supervised Learning - Classification/010 Logistic Regression Concepts.mp410.85MB
45. 05 Supervised Learning - Classification/011 Logistic Regression Model Development.mp4112.12MB
46. 05 Supervised Learning - Classification/012 Model Evaluation Concepts.mp483.47MB
47. 05 Supervised Learning - Classification/013 Model Evaluation - Calculating with Python.mp4174.04MB
48. 06 Supervised Learning - Regression/001 Simple and Multiple Linear Regression Concepts.mp4212.19MB
49. 06 Supervised Learning - Regression/002 Multiple Linear Regression - Model Development.mp475.59MB
50. 06 Supervised Learning - Regression/003 Evaluation Metrics - Concepts.mp449.47MB
51. 06 Supervised Learning - Regression/004 Evaluation Metrics - Implementation.mp4159.9MB
52. 06 Supervised Learning - Regression/005 Polynomial Linear Regression Concepts.mp426.39MB
53. 06 Supervised Learning - Regression/006 Polynomial Linear Regression Model Development.mp4219.12MB
54. 06 Supervised Learning - Regression/007 Random Forest Concepts.mp430.23MB
55. 06 Supervised Learning - Regression/008 Random Forest Model Development.mp4246.24MB
56. 06 Supervised Learning - Regression/009 Support Vector Regression Concepts.mp426.97MB
57. 06 Supervised Learning - Regression/010 Support Vector Regression Model Development.mp4121.01MB
58. 07 Unsupervised Learning - Clustering Techniques/001 Introduction.mp438.11MB
59. 07 Unsupervised Learning - Clustering Techniques/002 K-means Concepts1.mp444.53MB
60. 07 Unsupervised Learning - Clustering Techniques/003 K-means Concepts2.mp421.28MB
61. 07 Unsupervised Learning - Clustering Techniques/004 K-means Model Development1.mp435.98MB
62. 07 Unsupervised Learning - Clustering Techniques/005 K-means Model Development2.mp4103.83MB
63. 07 Unsupervised Learning - Clustering Techniques/006 K-means - Model Evaluation.mp4102.4MB
64. 07 Unsupervised Learning - Clustering Techniques/007 DBSCAN Concepts.mp426.85MB
65. 07 Unsupervised Learning - Clustering Techniques/008 DBSCAN Model Development.mp486.87MB
66. 07 Unsupervised Learning - Clustering Techniques/009 Hierarchical Clustering Concepts.mp424.29MB
67. 07 Unsupervised Learning - Clustering Techniques/010 Hierarchical Clustering Model Development.mp4145.89MB
68. 08 Hyper Parameter Optimization (Model Tuning)/001 Introduction.mp417.02MB
69. 08 Hyper Parameter Optimization (Model Tuning)/002 Support Vector Regression - Model Tuning.mp4125.61MB
70. 08 Hyper Parameter Optimization (Model Tuning)/003 K-Means - Model Tuning.mp415.3MB
71. 08 Hyper Parameter Optimization (Model Tuning)/004 k-NN - Model Tuning.mp4133.64MB
72. 08 Hyper Parameter Optimization (Model Tuning)/005 Overfitting and Underfitting.mp472.09MB