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In this video on Machine Learning with Python full course, you will understand the basics of machine learning, essential applications of machine learning, machine learning concepts and understand why mathematics, statistics, and linear algebra are crucial. We'll also learn about regularization, dimensionality reduction, PCA. We will perform a prediction analysis on the recently held US Elections. Finally, you will study the Machine Learning roadmap for 2021?

00:00:00 Machine Learning Basics
00:08:45 Top 10 applications of machine learning
00:13:40 Machine Learning Tutorial Part-1
0:14:26 Why Machine Learning
0:18:33 What is Machine Learning
0:25:15 Types of Machine Learning
0:25:27 Supervised Learning
0:27:47 Reinforcement Learning
0:29:07 Supervised vs Unsupervised Learning
0:39:23 Decision Trees
01:15:10 Machine Learning Tutorial Part-2
01:19:47 K-Means Algorithm
02:10:47 Mathematics for Machine Learning
2:11:15 What is Data?
02:12:07 Quantitative/Categorical Data
02:14:54 Qualitative/Categorical Data
02:15:12 Linear Algebra
02:38:01 Calculus
02:52:21 Statistics
03:05:16 Demo on Statistics
03:22:27 Probability
03:48:09 Demo on Naive Bayes
04:01:00 Linear Regression Analysis
04:20:37 Logistic Regression
04:38:35 Confusion Matrix
04:58:31 Decision Tree in Machine Learning
05:20:30 Random Forest
05:50:29 K Nearest Neighbors
06:16:56 Support Vector Machine
06:35:57 Regularization in ML
07:05:03 PCA
07:35:16 US Election Prediction
08:03:49 Machine Learning roadmap 2021

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