Introduction to Artificial Intelligence

This repository contains course notebooks and notes for Introduction to Artificial Intelligence.

Contents:

• Module 1: Introduction

  1. Introduction to the course
  2. Introduction to Artificial Intelligence
  3. Various applications of Artificial Intelligence
  4. Brief introduction to Natural Language Processing
  5. Vrief introduction to Computer Vision

• Module 2: Python and Required Toolkit

  1. Virtual enviornments and Installing anaconda
  2. Mastering Numpy
  3. Plotting using Matplotlib
  4. Data wrangling using Pandas
  5. Putting it all together

• Module 3: Introduction to Machine Learning

  1. Introduction to Machine Learning
  2. Introduction to Supervised learning
  3. Nearest Neighbours
  4. Support Vector Machines
  5. Random Forests
  6. Linear Regression
  7. Building Nearest Neighbours using Numpy.

• Module 4: Introduction to Deep learning

  1. Why Deep learning?
  2. Linear Regression
  3. Gradient Descent
  4. What are arrays, vectors and Tensors
  5. Neural Networks overview
  6. Backpropagation
  7. What it has to do with brain?

• Module 5: Building first project

  1. Getting to know the problem
  2. Trying simple Machine Learing concepts on the problem
  3. Applying Deep learning using Numpy
  4. Introduction to Keras
  5. Solving problem using Keras