Projects
Assignments
Overview
This course is an introduction to the modern AI and ML with equal emphasis on foundational concepts and practice on real world problems and will expose foundations of modern AI along with enough attention to the recent explosion of machine learning techniques.
Objectives
At the end of Intro to AI & ML training course, participants will be able to
Prerequisites
Basic Programming knowledge.
Course Outline
Problem Formulation and Solvingedforce2021-11-12T13:46:07+05:30
- Formulating real world problems as AI and ML problems
- Classification and Regression Problems
- Intuitive and Simple Algorithms: KNN, Decsion Tree and Simple Linear Classifier
- Representation of the world and real data: Emphasis on Text, Image, Speech and Sequences
- Visualization, Data Preparation and Unsupervised Learning
- End to end Problem Solving: Navigating through three specific problems and case studies
Closer Look at AIML Algorithmsedforce2021-11-12T13:46:58+05:30
- Simple Linear Algorithms, Optimization and Training
- Non linear Solutions and MLP
- Gradient Descent and Backpropagation
- Decision Tree, Random Forest and Ensembles
- Principles and Practice of ML:
- Training, Validation and Testing
- Overfitting and Regularization
- Errors, Performance Metrics and Reliable Error Estimates
- Support Vector Machines and Kernels
Deep Learning and Practical Issuesedforce2021-11-12T13:48:10+05:30
- Introduction to DL and Toolchain
- Convolutional Neural Networks
- Auto Encoders
- Recurrent Neural Networks
- Selected Special Topics
- Human In the Loop Solutions and Deployment
