Scikit-Learn Course - Machine Learning in Python Tutorial

Video tutorial on machine learning with the scikit-learn library in Python. Covers installing SKlearn, plotting graphs, features and labels, saving and loading models, train/test splits, and classification. Explains and demonstrates KNN, SVM, linear regression, logistic regression and KMeans clustering, then moves to neural networks: overfitting and underfitting, backpropagation, cost functions and gradient descent, convolutional networks, and a handwritten digit recognizer project. Suited to programmers new to machine learning who already have basic Python.

Syllabus

Introduction.
Installing SKlearn.
Plot a Graph.
Features and Labels_1.
Save and Open a Model.
Classification.
Train Test Split.
What is KNN.
KNN Example.
SVM Explained.
SVM Example.
Linear regression.
Logistic vs linear regression.
Kmeans and the math beind it.
KMeans Example.
Neural Network.
Overfitting and Underfitting.
Backpropagation.
Cost Function and Gradient Descent.
CNN.
Handwritten Digits Recognizer.