Introduction
Learn simple and efficient tools for data mining and data analysis, using Python’s Machine Learning framework Scikit-learn. Master concepts such as regression, clustering, dimensionality reduction, preprocessing, decision trees and neural networks and more.
Course Outline
Course Outline
- Getting Started on Scikit-Learn
- What is Machine Learning
- Machine Learning Steps
- What is Scikit-Learn
- Installing Scikit-Learn
- Datasets
- What is Dataset
- Iris Dataset
- Handwritten Digits Dataset
- Boston Housing Price Dataset
- Splitting Datasets for Training/Testing
- Supervised Learning
- What is Supervised Learning
- Key Classifiers Algorithms – KNN, SVM, GNB, DT, Ensemble
- Performance Metric and Errors
- Model Persistence
- Regression
- Unsupervised Learning
- What is Unsupervised Learning
- Key Clustering Algorithms – K-Means, Mean Shift, Agglomerative
- Dimensionality Reduction – PCA
- Neural Network
- What is Neural Network?
- Multi Layer Perceptron Classifier
- Hidden Layers
- Activation Function
- Solver
- Learning Rate
- Momentum