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127B |
1. Decision Tree Classifier.mp4 |
65.01MB |
1. Evaluation Metrics.mp4 |
60.33MB |
1. Handling Missing Values in Python.mp4 |
63.56MB |
1. Installation of Python.mp4 |
68.61MB |
1. Introduction Machine Learning Using Python.mp4 |
48.69MB |
1. Linear Regression in ML.mp4 |
82.93MB |
2. Example of Evaluation Metrics.mp4 |
97.85MB |
2. Example of Machine Learning Using Python.mp4 |
70.23MB |
2. Handling Missing Values in Python Continues.mp4 |
72.27MB |
2. Linear Regression Example.mp4 |
64.70MB |
2. Random Forest Classification.mp4 |
56.26MB |
3. Confusion Matix in Evaluation Metrics.mp4 |
55.58MB |
3. Example of Machine Learning Using Python Continues.mp4 |
34.55MB |
3. Exception Handling in Python.mp4 |
56.35MB |
3. K Mean Clustering.mp4 |
67.22MB |
3. Linear Regression Example Continues.mp4 |
79.73MB |
4. Apriori Python Package.mp4 |
74.52MB |
4. Classification Reports in Evaluation Metrics.mp4 |
116.80MB |
4. More on Exception Handling in Python.mp4 |
58.70MB |
4. Support Vector Algorithm in ML.mp4 |
81.52MB |
5. Apriori Python Package Continues.mp4 |
74.46MB |
5. Example of MAE, MSE and Variance using Evaluation Metrics.mp4 |
74.89MB |
6. Sea Born Example using Evaluation Metrics.mp4 |
63.54MB |
7. Scatter Matrix using Evaluation Metrics.mp4 |
33.77MB |