Machine Learning with Python

Course Description

The objective of this course is to give you a holistic understanding of machine learning, covering theory, application, and inner workings of supervised, unsupervised, and deep learning algorithms.

In this series, we'll be covering linear regression, K Nearest Neighbors, Support Vector Machines (SVM), flat clustering, hierarchical clustering, and neural networks.

Machine Learning with Python
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Video Lectures & Study Materials

Visit the official course website for more study materials: https://pythonprogramming.net/machine-learning-tutorials/

# Lecture Play Lecture
1 Introduction to Machine Learning Play Video
2 Regression Intro Play Video
3 Regression Features and Labels Play Video
4 Regression Training and Testing Play Video
5 Regression forecasting and predicting Play Video
6 Pickling and Scaling Play Video
7 Regression How it Works Play Video
8 How to program the Best Fit Slope Play Video
9 How to program the Best Fit Line Play Video
10 R Squared Theory Play Video
11 Programming R Squared Play Video
12 Testing Assumptions Play Video
13 Classification w/ K Nearest Neighbors Intro Play Video
14 K Nearest Neighbors Application Play Video
15 Euclidean Distance Play Video
16 Creating Our K Nearest Neighbors A Play Video
17 Writing our own K Nearest Neighbors in Code Play Video
18 Applying our K Nearest Neighbors Algorithm Play Video
19 Final thoughts on K Nearest Neighbors Play Video
20 Support Vector Machine Intro and Application Play Video
21 Understanding Vectors Play Video
22 Support Vector Assertion Play Video
23 Support Vector Machine Fundamentals Play Video
24 Support Vector Machine Optimization Play Video
25 Creating an SVM from scratch Play Video
26 SVM Training Play Video
27 SVM Optimization Play Video
28 Completing SVM from Scratch Play Video
29 Kernels Introduction Play Video
30 Why Kernels Play Video
31 Soft Margin SVM Play Video
32 Soft Margin SVM and Kernels with CVXOPT Play Video
33 SVM Parameters Play Video
34 Clustering Introduction Play Video
35 Handling Non-Numeric Data Play Video
36 K Means with Titanic Dataset Play Video
37 Custom K Means Play Video
38 K Means from Scratch Play Video
39 Mean Shift Intro Play Video
40 Mean Shift with Titanic Dataset Play Video
41 Mean Shift from Scratch Play Video
42 Mean Shift Dynamic Bandwidth Play Video

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