Artificial Intelligence (AI)

Module 1 - Introduction To Machine Learning

Basic Concept

Train,Test & Validation Distribution

ML Strategy

Computation Graph

Evaluation Metric

Human Level Performance

Module 2 - Machine Learning

Supervised

Linear Regression

Logistic Regression

Gradient Descent

Decision Tree

Random Forest

Bagging & Boosting

KNN

Unsupervised

K-Means

Hierarichal Clustering

Module 3 - Python Programming

Python

Basic Programming

NLP Libraries

OpenCV

Module 4 - Mathematics Foundation

Basic Statistics

Sampling & Sampling Statistics

Hypothesis Testing

Calculus

Derivatives

Optimization

Linear Algebra

Function

Scalar-Vector-Matrix

Vector Operation

Probability

Space

Probability

Distribution

Module 5 - Intro To Neural Network & Deep Learning

Introduction

Intro

Deep Learning Importance [Strength & Limiltation]

SP | MLP

Feed Forward & Backward Propagation

Neural Network Overview

Neural Network Representation

Activation Function

Loss Function

Importance of Non-linear Activation Function

Gradient Descent for Neural Network

Module 6 - Parameter & Hyperparameter

Practical Aspect

Train, Test & Validation Set

Vanishing & Exploding Gradient

Dropout

Regularization

Optimization

Bias Correction

RMS Prop

Adam,Ada,AdaBoost

Learning Rate

Tuning

Softmax

Module 7 - Data Processing

Environment

Scikit Learn

NLTK

Spacy & Gensim

OpenCV

Tensorflow

Keras

Text Processing

Representation

Data Cleaning

Data Preprocessing

Similarity

Image Processing

Image

Image Transformation

Filters

Noise Removal

Correlation & Convolution

Edge Detection

Non Maximum Suppression & Hysterisis

Fourier Domain

Video Processing

Speech Data Analytics

Feature Extraction

Image Feature

Descriptors

Object Detection

Detection  & Classification

Module 8 – CNN

CNN

Computer Vision

Padding

Convolution

Pooling

Why Convolution

Deep Convolution Model

Case Studies

Classic Networks

Inception

Open Source Implementation

Transfer Learning

Detection Algorithm

Object Localization

Landmark Detection

Object Detection

Bounding Box Prediction

Yolo

Face Recognition

What is Face Recognition

One Shot Learning

Siamese Network

Triplet Loss

Face Verification

Neural Style Transfer

Deep Conv Net Learning

Module 9 - RNN

Why Sequence Model

RNN Model

Backpropogation through time

Different Type of RNNs

GRU

LSTM

Biderectional LSTM

Deep RNN

Word Embedding

Debiasing

Negative Sampling

Elmo & Bert

Beam Search

Attention Model

Module 10 - Generative Adversial Network

Autoencoders & Decoders

Adversial Network

Active Learning

Module 11 - Reinforcement Learning

Q Learning

Exploration & Exploitation

Module 12 - Assignments

Introduction to Machine Learning

Business Case evaluation

Data requirements and collection

Evaluation metrics

Machine Learning

Profit of 50_startups data prediction

Extra marital affair prediction

Fraud data analytics

Fabric sales analysis

Classification of animals data

Crime data analysis using clustering method and airlines data to obtain optimum number of clusters.

Python Programming

Resource Information Analysis

Text Cleaning of Customer reviews using NLP

Image Manipulation (Loading, Rotation etc.)

Mathematics Foundation

Sampling & Sampling Statistics

Hypothesis Testing

Calculus Problems

Linear Algebra Problems

Probability Problems

Intro to Neural Network & Deep Learning

Parameter & Hyperparameter

Risk Evaluation

Prediction of claim amount

Emotor temp prediction

User Behavioural Pattern

(2 ANN assignments+ 2 Parameter and hyperparameters)

Data Processing

User review data load and familiriaty with data and environment

E commerce Product Similarity

Sentiment classification of movie reviews

Emotion Mining of user reviews"

Vehicle edge detection

Cleaning of hand-written digits data

Image data Augumentation

Facial feature detection

Image data wrangling for classification

Video Analysis of a short film

Speech data Analysis w.r.t emotion

CNN

Ecommerce product image classification

Disease prediction based on images

(2 CNN algorithms)

Vehicle identification(Object Detection)

Animal Classification(Object Classification)

Spatial Image classification (Image segmentation)

Face detection

Face recognition (Attendance using facial recognition)

RNN

Next word prediction (Vanilla RNN)

Twitter data analysis using Named Entity Recognition(NER)

Retail data - Word2vec

NER and Forecasting of Oil price prediction

Auto text composer (NER language model)

Auto text composer (NER language model)

Q and A Chatbot

Real life voice Recognition

Generative

Machine Translation

New Image generation based on existing images

Reinforcement Learning

Game Intelligence

Module 13 - Projects

1.Chatbot project

Build end to end chatbot right from data storage schema to final output for a domain

2.Emotion Analytics

Identifying and analyzing the full spectrum of human emotions including mood, attitude and emotional personality.

3.Object Detection

Detection of objects in images

4.Face detection from CC camera feed

Analysis of video feed from CC cameras