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Understanding Machine Learning

person icon PARTHA MAJUMDAR

4.6

Understanding Machine Learning

This course provides introduction to how Machine Learning Models are created.

updated on icon Updated on Apr, 2024

language icon Language - English

person icon PARTHA MAJUMDAR

category icon Development,Machine Learning,Data Science

Lectures -6

Resources -1

Duration -1.5 hours

4.6

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Course Description

Machine Learning is becoming ubiquitous across all industries. Already many applications have been identified which use Machine Learning now. Few examples include Spam Detection, Face Recognition, Emotion Analysis, Object Detection, Credit Card Fraud Detection, Weather Prediction, and the list is almost endless. More new applications are being identified by different industries almost everyday.

It is not just about applying superior technology for traditional problems when we apply Machine Learning. It is also about business sense since applying Machine Learning, we can make experiments and applications much more economical.

This course is a result of a discussion among my Project Team from our cohort in IIT, Kanpur learning Cyber Security. We have embarked to create a product for Malware Detection using Machine Learning. While all of us are getting grips on Malware Analysis, the team needed some inputs of Machine Learning. To fill the gap, I conducted some sessions with our Project Team members on Machine Learning. This course is a collection of the recording of these sessions.

This course discusses what are Machine Learning Algorithms. We discuss Random Forest Algorithm and Linear Regression as examples to understand what are models in Machine Learning. We see how to implement such models using Python. During the discussion on the development of the Machine Learning models, we discuss the various steps like Data Preprocessing, Normalisation, Scaling, etc. We touch upon the basics of Neural Network and take a slight deep dive into Regression. The course includes discussion on concepts like what is overfitting, what is hyper-parameter tuning, etc.

This course tries to give an idea for what it takes to create a product which uses Machine Learning. I believe that the discussions can get one started to apply Machine Learning to many problems.

Goals

What will you learn in this course:

  • What are models in Machine Learning?
  • How to build models for Machine Learning?
  • How does Machine Learning build a Linear Regression model?

Prerequisites

What are the prerequisites for this course?

  • Some knowledge of programming in any language is essential.
Understanding Machine Learning

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction
1 Lectures
  • play icon Welcome to the Course 04:22 04:22
Lectures
3 Lectures
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Course Closing
1 Lectures
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Instructor Details

PARTHA MAJUMDAR

PARTHA MAJUMDAR

Partha started his career in 1989 as a programmer. In his first assignment, he was involved in development of a Cricket Tournament management system as a part of the team from Centre for Development of Telematics (C-DOT) requested by the Prime Minister of India, Mr. Rajiv Gandhi. Since then Partha has developed Tea Garden automation solution, Hospital Management solution, Travel Management solution, Manufacturing Resource Planning (MRP II) solution, Insurance Management solution and Tax automation solution (for Government of Thailand).

Partha got involved in Telecom solution with project from Total Access Communications, Bangkok in 1996. Partha developed the completed solution architecture and designed & developed the complete infrastructure services and primitives on top of which the end-to-end Customer Care and Billing solution was developed between 1996-1998.

Partha has worked for companies including Amdocs, Portal, Siemens and has developed key components of their solutions. For Siemens, Partha developed the complete BSS suite.

Partha worked with Mobily, Saudi Arabia as the Enterprise Architect and has first-hand of experience of work inside a Telecom Operator.

Partha started his own company, Majumdar Consultancy Pvt Ltd, in 2014. He partnered with a Dubai based businessman to open SI Solutions India Pvt Ltd in 2016. In 2019, he joined Tools and Solutions, Saudi Arabia as Director - Professional Services to establish the Professional Services business.

Partha has recently developed a Remote Control, which can be controlled from a Web Site. The Remote Control can in turn control any device. The Remote Control to be controlled needs having Infra-Red sensing capabilities. The Remote Control is controlled through DragonBoard 410C through a Android Program.

Partha has been working on fine tuning the algorithm for a Access Control System through Face Recognition. The program has been developed using Convolutional Neural Network (CNN).

Partha has also developed a software which tries to predict the Stock Market. The solution has been developed using Recurrent Neural Network (RNN). The solution presently predict with an accuracy of 77%.

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