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ee524's Introduction

Welcome to EE524 (Jul-Nov 2020)

Hello friends... Hope you are safe and sound.

I hope you are all excited to learn about Machine Learning. In this semester, you must be going through the Machine Learning Course offerred by Professor Manas Kamal Bhuyan sir.

This is the official course webpage for the course EE524 Machine Learning Laboratory which will complement the course Introduction to Machine Learning. We will be using Python an open source software to run our codes.

import numpy as np
import tensorflow as tf
for i in range(10):
  print(i)

As mentioned, in the instruction manual we will also use libraries like Numpy, Matplotlib, Pandas and Scikit-Learn.

A breakthrough in Machine Learning

would be worth 10 microsofts.

-Bill Gates

A baby learns to crawl, walk and then run.

We are in the crawling stage, when it comes to applying Machine Learning.

-Dave Waters

Objectives of this lab:

  1. Learn about the concepts in Machine Learning from data generation, handling, preprocessing.
  2. Learn about different algorithms in Machine Learning.
  3. Improve coding skills in Python.
  4. Implement these concepts on your own.
  5. Create something as an outcome of this lab course.

Lab evaluation Structure:

  • Continuous Evaluations: 50 Marks (Through Assignments)
  • Viva: 20 Marks (After all submissions)
  • Mini Project: 30 Marks (Will be given after 6th Lab Session)

Timeline:

We have a total of 12 labs in this session. Everything will be online due to the pandemic. We will try to complete most of the important algorithms required for you to have a good background in Machine Learning. We will be pushing assignments, have doubt sessions and will evaluate your assignments. Assignments will be weekly.

Announcements:

  • 7th Sept 2020: Assignment 1 has been released
  • 11th Sept 2020: Doubt Session for Assignment 1 is over
  • 17th Sept 2020: Assignment Submission link is released
  • 20th Sept 2020: Submission Deadline for Assignment 1

Assignments:

  1. Assignment 1 (Ungraded): Fundamentals of Python Release Date: 7th September 2020 Doubt Session: 11th September 2020 Submission Date: 20th September 2020 Instruction Manual | PDF | Resources | Solution | Colab Notebook

  2. Assignment 2:

Team communication:

  1. Slack Channel EE524 (For conversation and doubts)
  2. Moodle Link (Theory course)
  3. Outlook Group
  4. Github Repository (For submitting assignments)

Resources:

  1. Python Course
  2. Youtube Machine Learning and Coursera Machine Learning
  3. NPTEL PK Biswas Pattern Recognition
  4. Numpy Tutorial
  5. Pandas Tutorial
  6. Matplotlib Tutorial
  7. Youtube channels for your reference: Socratica| SentDex| Siraj Raval|

Teaching Assistants:

Nadeem Atif

Nadeem Atif: Research Scholar, EEE Department, IIT Guwahati | Email: [email protected] | Contact: 7302099843

Snehil Sanyal

Snehil Sanyal: Research Scholar, EEE Department, IIT Guwahati | Email: [email protected] | Contact: 9399690211

H Balaji: M.Tech 2nd year, EEE Department, IIT Guwahati | Email: [email protected] | Contact: 9441791359

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