Complete Machine Learning In 6 Hours| Krish Naik

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github.com/krishnaik06/The-Grand-Complete-Data-Sci…

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Time Stamp:

00:00:00 Introduction
00:01:25 AI Vs ML vs DL vs Data Science
00:07:56 Machine LEarning and Deep Learning
00:09:05 Regression And Classification
00:18:14 Linear Regression Algorithm
01:07:14 Ridge And Lasso Regression Algorithms
01:33:08 Logistic Regression Algorithm
02:13:52 Linear Regression Practical Implementation
02:28:30 Ridge And Lasso Regression Practical Implementation
02:54:21 Naive Baye's Algorithms
03:16:02 KNN Algorithm Intuition
03:23:47 Decision Tree Classification Algorithms
03:57:05 Decision Tree Regression Algorithms
04:02:57 Practical Implementation Of Deicsion Tree Classifier
04:09:14 Ensemble Bagging And Bossting Techniques
04:21:29 Random Forest Classifier And Regressor
04:29:58 Boosting, Adaboost Machine Learning Algorithms
04:47:30 K Means Clustering Algorithm
05:01:54 Hierarichal Clustering Algorithms
05:11:28 Silhoutte Clustering- Validating Clusters
05:17:46 Dbscan Clustering Algorithms
05:25:57 Clustering Practical Examples
05:35:51 Bias And Variance Algorithms
05:43:44 Xgboost Classifier Algorithms
06:00:00 Xgboost Regressor Algorithms
06:19:04 SVM Algorithm Machine LEarning Algorithm
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