Webinar

A webinar where I explain about the basic math concepts in ML and DL. Attended by more than 200+ students all over India and got a very good feedback.

Watch in youtube - link

Ml and DL Webinar

Webinar on Machine Learning and Deep Learning - The math you need to get started. Organized by: ECE Department and Networking club.

youtube

Github repo for all the resources and a blog post for future reference

bharathikannann/Python

Artificial intelligence (AI) is the broad science of mimicking human abilities, machine learning is a specific subset of AI that trains a machine how to learn. Machine learning is a field of study that gives computers the ability to learn without being explicitly(clearly) programmed.

bharathikannann

Organized by:
ECE Department and Networking club, Sri Eshwar College of Engineering, Coimbatore, Tamil Nadu.
Resource Person
  N Bharathi kannan, IV ECE.
Staff Cordinators
  Mr. J. Dhanasekar, AP/ECE,
  Mr.S. Deepak, AP/ECE.
Student Cordinators
  M Anish, IV ECE,
  S Mantharagiri, III ECE.
College website : sece.ac.in

Table of contents (blog)

• Machine Learning
  • Machine Learning Algorithms
  • Supervised Learning
    • Linear Regression
      • Hypothesis Function
      • Cost Function
      • Gradient Descent
      • Linear Regression from scratch in python
      • Multiple Variables
      • Polynomial Regression
    • Logistic Regression
    • One Vs All
    • Regularization
    • Vectorization
  • Unsupervised Learning
    • Clustering
    • Application
  • Reinforcement Learning

• Deep Learning
  • Neural Networks
    • Neural Networks from scratch in python
  • Convolutional Neural Networks
  • Recurrent Neural Networks

Regression Visualization online links :

These can we viewed without installing the software

• Linear Regression and Polynomial Regression 2D - link

• Linear Regression and Polynomial Regression 3D - link

• Logistic Regression 2D - link

• Logistic Regression 3D - link 

Linear Regression Code in Scikit-learn notebook + Exercise

bharathikannann/Python

It includes two problems with datasets taken from kaggle and implemented for you. Includes 1 exercise for practice.

bharathikannann

Linear Regression Code from Scratch notebook

bharathikannann/Python

Linear Regression Implemented from scratch in python to understand how it works. However it is not efficient as implemented using Scikit-learn.

bharathikannann

Important links

Try experimenting with learning rate (∝)

Optimizing Learning Rate

Experiment with different learning rates and see how they affect the number of steps required to reach the minimum of the loss curve. Try the exercises below the graph.

developers.google.com

Reinforcement learning

Google atari breakout youtube video

Alpha go Documentary

AlphaGo - Full Documentary

With more board configurations than there are atoms in the universe, the ancient Chinese game of Go has long been considered a grand challenge for artificial in...

youtube

Multi Agent Hide and Seek game from Open AI

Tensorflow Playground

Neural Network Playground

It's a technique for building a computer program that learns from data. It is based very loosely on how we think the human brain works.

developers.google.com

Neural Networks from scratch code (bonus)

bharathikannann/Python

A Neural Network implemented from scratch in python to understand how it works.

bharathikannann

Convolutional Neural Networks

Live demo

CNN Explainer

An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs).

poloclub.github.io

References

• Machine Learning course by Andrew NG (coursera)

• Deep Learning Specialization by Andrew NG (coursera)

• Machine Learning crash course from google