Implementing Commonly Used Machine Learning Algorithms using Scikit-Learn

Welcome to this video on machine learning.
1 - What Are The Prerequisites For Machine Learning?
2 - Linear Regression
References -
a.https://towardsdatascience.com/linear-regression-detailed-view-ea73175f6e86
b. https://brilliant.org/wiki/linear-regression
3 - Linear Regression Python Implementation with Scikit-Learn
Introduction To Linear Regression : https://tinyurl.com/lregfull
Link To GitHub Repo : https://tinyurl.com/lregsci
Blog for code reference : https://tinyurl.com/bloglrimplemen
4 - Logistic Regression in Machine Learning
Blog for references :
a. https://www.internalpointers.com/post/cost-function-logistic-regression
b. https://www.geeksforgeeks.org/understanding-logistic-regression/
c. https://www.datacamp.com/community/tutorials/understanding-logistic-regression-python
5 - Logistic Regression Python Implementation with Scikit-Learn
6 - Introduction to Support Vector Machines (SVM)
7 - Support Vector Machines (SVM) in Scikit-learn
8 - Understanding Random Forest
9 - Implement Random Forest Using the Scikit-Learn
The dataset can be downloaded from here - https://drive.google.com/file/d/13nw-uRXPY8XIZQxKRNZ3yYlho-CYm_Qt/view
More info about the dataset -
https://archive.ics.uci.edu/ml/datasets/banknote+authentication
10 - Understanding K-Means Clustering
11 - K-Means Clustering with scikit-learn Python Example
12 - K-Nearest Neighbours (KNN algorithm)
13- K-Nearest Neighbours (KNN algorithm) implementation in Scikit-Learn

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