Definition, History, Need, Features

Block Diagrammatic of Machine Learning

Arrangements of learning machine

Classification of machine learning

Supervised learning

Unsupervised learning

Reinforcement learning

Lifecycle of machine learning

Application of machine learning

Dimensionality Reduction-Definition

Row vector and column vector

How to represent a dataset

How to represent a dataset

Data Preprocessing in machine learning

Feature normalization

Mean of a data matrix

Column standalization

Co-variance of a data matrix

Principal Component Analysis for dimensionality reduction

supervised learning : Definition, How it works

Types of Supervised Learning Algorithms-K-Nearest Neighbours,

Naive Bayes , decision Trees,

Linear Regression, Logistic Regression, Support Vector Machines

Unsupervised Learning : Clustering, K-mean,Ensemble methods

Evaluation- Performance Measurement of models in terms of accuracy

Confusion Matrix, Precision & recall, F1-score, Receiver operating

Booting, Bagging, Random Forests

Characteristics curve(ROC) curve and AUC

Medium absolute deviation (MAD)

Distribution Of errors