Introduction |
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ML-Introduction |
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00:23:00 |
Basic Statistics |
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ML-Basic Statistics-1 |
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00:44:00 |
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ML-Basic Statistics-2 |
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00:43:00 |
Data Cleaning |
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ML-Data Cleaning-1 |
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00:38:00 |
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ML-Data Cleaning-2 |
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00:38:00 |
Regression Analysis |
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ML-Regression Analysis-1 |
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01:03:00 |
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ML-Regression Analysis-2 |
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01:00:00 |
Logistic Regression |
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ML-Logistic Regression |
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01:00:00 |
Decision Trees |
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ML-Decision Tree-1 |
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00:54:00 |
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ML-Decision Tree-2 |
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00:44:00 |
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ML-Decision Tree-3 |
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01:01:00 |
Model Selection And Cross Validation |
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ML-Model Selection |
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00:47:00 |
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ML-Cross Validation |
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00:42:00 |
Ensemble Models |
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ML-Ensemble Model – Random Forest |
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01:07:00 |
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ML-Ensemble Model – Boosting |
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00:43:00 |
Feature Engineering |
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ML-Feature Engineering |
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00:52:00 |
Natural Language Processing |
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ML-NLP and Text Mining |
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01:07:00 |
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ML-Sentiment Anlaysis |
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00:31:00 |
Testing of Hypothesis |
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ML-Testing of Hypothesis |
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00:54:00 |
End to End ML Project |
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ML-End to End Project-1 |
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00:29:00 |
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ML-End to End Project-2 |
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00:30:00 |
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ML-End to End Project-3 |
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00:29:00 |
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ML-End to End Project-4 |
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00:24:00 |