GigaCourse Com Udemy - The Supervised Machine Learning Course

1. 1 - Introduction/1 - Introduction.mp469.89MB
2. 2 - Setting up the Environment/2 - Installing Anaconda.mp429.53MB
3. 2 - Setting up the Environment/3 - Jupyter Dashboard Part 1.mp410.25MB
4. 2 - Setting up the Environment/4 - Jupyter Dashboard Part 2.mp420.99MB
5. 2 - Setting up the Environment/5 - Installing the relevant packages.mp422.78MB
6. 3 - Naïve Bayes/10 - The HamorSpam Example.mp466.89MB
7. 3 - Naïve Bayes/12 - The YouTube Dataset Creating the Data Frame.mp433.75MB
8. 3 - Naïve Bayes/13 - CountVectorizer.mp436.99MB
9. 3 - Naïve Bayes/14 - The YouTube Dataset Preprocessing.mp443.97MB
10. 3 - Naïve Bayes/16 - The YouTube Dataset Classification.mp423.67MB
11. 3 - Naïve Bayes/18 - The YouTube Dataset Confusion Matrix.mp417.79MB
12. 3 - Naïve Bayes/19 - The YouTube Dataset Accuracy Precision Recall and the F1 score.mp437.74MB
13. 3 - Naïve Bayes/20 - The YouTube Dataset Changing the Priors.mp440.34MB
14. 3 - Naïve Bayes/6 - Motivation.mp443.38MB
15. 3 - Naïve Bayes/7 - Bayes Thought Experiment.mp433.66MB
16. 3 - Naïve Bayes/9 - Bayes Theorem.mp465.92MB
17. 4 - KNearest Neighbors/22 - Motivation.mp424.43MB
18. 4 - KNearest Neighbors/23 - Math Prerequisites Distance Metrics.mp427.79MB
19. 4 - KNearest Neighbors/24 - Random Dataset Generating the Dataset.mp416.85MB
20. 4 - KNearest Neighbors/25 - Random Dataset Visualizing the Dataset.mp428.19MB
21. 4 - KNearest Neighbors/26 - Random Dataset Classification.mp450.6MB
22. 4 - KNearest Neighbors/27 - Random Dataset How to Break a Tie.mp426.76MB
23. 4 - KNearest Neighbors/28 - Random Dataset Decision Regions.mp446MB
24. 4 - KNearest Neighbors/29 - Random Dataset Choosing the Best Kvalue.mp432.64MB
25. 4 - KNearest Neighbors/30 - Random Dataset Grid Search.mp427.88MB
26. 4 - KNearest Neighbors/31 - Random Dataset Model Performance.mp421.21MB
27. 4 - KNearest Neighbors/33 - Theory with a Practical Example.mp443.75MB
28. 4 - KNearest Neighbors/34 - KNN vs Linear Regression A Linear Problem.mp446.73MB
29. 4 - KNearest Neighbors/35 - KNN vs Linear Regression A Nonlinear Problem.mp433.11MB
30. 4 - KNearest Neighbors/37 - Pros and Cons.mp455.22MB
31. 5 - Decision Trees and Random Forests/38 - What is a Tree in Computer Science.mp434.84MB
32. 5 - Decision Trees and Random Forests/39 - The Concept of Decision Trees.mp431.62MB
33. 5 - Decision Trees and Random Forests/40 - Decision Trees in Machine Learning.mp447.34MB
34. 5 - Decision Trees and Random Forests/41 - Decision Trees Pros and Cons.mp469.13MB
35. 5 - Decision Trees and Random Forests/42 - Practical Example The Iris Dataset.mp421.83MB
36. 5 - Decision Trees and Random Forests/43 - Practical Example Creating a Decision Tree.mp432.83MB
37. 5 - Decision Trees and Random Forests/44 - Practical Example Plotting the Tree.mp442.97MB
38. 5 - Decision Trees and Random Forests/45 - Decision Tree Metrics Intuition Gini Inpurity.mp453.2MB
39. 5 - Decision Trees and Random Forests/46 - Decision Tree Metrics Information Gain.mp426.36MB
40. 5 - Decision Trees and Random Forests/47 - Tree Pruning Dealing with Overfitting.mp439.41MB
41. 5 - Decision Trees and Random Forests/48 - Random Forest as Ensemble Learning.mp431.99MB
42. 5 - Decision Trees and Random Forests/49 - Bootstrapping.mp429.92MB
43. 5 - Decision Trees and Random Forests/50 - From Bootstrapping to Random Forests.mp425.93MB
44. 5 - Decision Trees and Random Forests/51 - Random Forest in Code Glass Dataset.mp452.81MB
45. 5 - Decision Trees and Random Forests/52 - Census Data and Income Preprocessing.mp459.6MB
46. 5 - Decision Trees and Random Forests/53 - Training the Decision Tree.mp427.35MB
47. 5 - Decision Trees and Random Forests/54 - Training the Random Forest.mp427.17MB
48. 6 - Support Vector Machines/55 - Introduction to Support Vector Machines.mp462.4MB
49. 6 - Support Vector Machines/56 - Linearly separable classes hard margin problem.mp459.15MB
50. 6 - Support Vector Machines/57 - Nonlinearly separable classes soft margin problem.mp449.84MB
51. 6 - Support Vector Machines/58 - Kernels Intuition.mp477.05MB
52. 6 - Support Vector Machines/59 - Intro to the practical case.mp431.54MB
53. 6 - Support Vector Machines/60 - Preprocessing the data.mp415.06MB
54. 6 - Support Vector Machines/61 - Splitting the data into train and test and rescaling.mp416.4MB
55. 6 - Support Vector Machines/62 - Implementing a linear SVM.mp412.66MB
56. 6 - Support Vector Machines/63 - Analyzing the results– Confusion Matrix Precision and Recall.mp428.22MB
57. 6 - Support Vector Machines/64 - Crossvalidation.mp476.47MB
58. 6 - Support Vector Machines/65 - Choosing the kernels and C values for crossvalidation.mp418.81MB
59. 6 - Support Vector Machines/66 - Hyperparameter tuning using GridSearchCV.mp435.14MB
60. 7 - Ridge and Lasso Regression/68 - Regression Analysis Overview.mp429.41MB
61. 7 - Ridge and Lasso Regression/69 - Overfitting and Multicollinearity.mp428.15MB
62. 7 - Ridge and Lasso Regression/70 - Introduction to Regularization.mp425.96MB
63. 7 - Ridge and Lasso Regression/71 - Ridge Regression Basics.mp443.16MB
64. 7 - Ridge and Lasso Regression/72 - Ridge Regression Mechanics.mp446.67MB
65. 7 - Ridge and Lasso Regression/73 - Regularization in More Complicated Scenarios.mp421MB
66. 7 - Ridge and Lasso Regression/74 - Lasso Regression Basics.mp421.63MB
67. 7 - Ridge and Lasso Regression/75 - Lasso Regression vs Ridge Regression.mp433.86MB
68. 7 - Ridge and Lasso Regression/76 - The Hitters Dataset Preprocessing and Preparation.mp446MB
69. 7 - Ridge and Lasso Regression/77 - Exploratory Data Analysis.mp436.96MB
70. 7 - Ridge and Lasso Regression/78 - Performing Linear Regression.mp452.93MB
71. 7 - Ridge and Lasso Regression/79 - Crossvalidation for Choosing a Tuning Parameter.mp430.49MB
72. 7 - Ridge and Lasso Regression/80 - Performing Ridge Regression with Crossvalidation.mp430.97MB
73. 7 - Ridge and Lasso Regression/81 - Performing Lasso Regression with Crossvalidation.mp430.96MB
74. 7 - Ridge and Lasso Regression/82 - Comparing the Results.mp430.97MB
75. 7 - Ridge and Lasso Regression/83 - Replacing the Missing Values in the DataFrame.mp421.22MB