Definition, Concepts, Terminology, Lifecycle

Problem categories of Machine Learning:

Classification

Clustering

Regression

Optimization

Learning Sub-Fields

Supervised

Unsupervised

Semi - Supervised

Reinforcement

Deep Learning

Basic Performance measures :

MSE, MAE, NMSE

ROC / AUC

Confusion Matrix

Accuracy

Precision / Recall etc

Environment Set Up Machine Learning (Anaconda Distribution)

Supervised Algorithms:

Linear

Logistic

CART

Naive Bayes

KNN

Decision Tree

Random Forest

SVM

Industrial Case Study

Unsupervised Algorithms:

K-Means

PCA

Industrial Case Study

Recommender Systems

Dimensionality Reduction

Arrays and Matrices

ND-array Object

Array Indexing

Datatypes

Array Math

Broadcasting

Std Deviation

Conditional Probability

Covariance and Correlation

Builds on NumPy

SciPy and its characteristics

SciPy and its Sub-Packages

Cluster

fftpack

Linalg

Signal

Integrate

Optimize

Statistics: Baye’s Theorem using SciPy

Plotting Graphs and Charts

Line Chart

Pie Chart

Bar Chart

Scatter Plot

Histograms

3-D Plots

Subplots

The Matplotlib API

Dataframes

NumPy array to a dataframe

Import Data (CSV, JSON, EXCEL, SQL Databases) Data operations:

View

Select

Filter

Sort

3GroupBy

Cleaning

Join/Combine

Handling Missing Values

Introduction to Natural Language Processing (NLP) ~ NLTK package

Text Processing:

Tokenization

Stemming

Lemmatization

Stop Word Removal

Text Feature Engineering:

Syntactical Parsing

Entity Parsing

Statistical Features

NLP Applications

Text Mining with Python(Web Scraping)

Text Analysis

Case Study-Sentiment Analysis with Twitter

Deep Learning ( Tensorflow ) Overview

Computer Vision Overview

Chat bot overview

Important Scientific Research Papers.