Udemy

Machine Learning For Researchers

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  • 17,115 Students
  • Updated 6/2020
4.4
(132 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Duration
5 Hour(s) 35 Minute(s)
Language
English
Taught by
Academy of Computing & Artificial Intelligence, Kaneeka Vidanage
Rating
4.4
(132 Ratings)
2 views

Course Overview

Machine Learning For Researchers

Learn Research Methods & Machine Learning

Indicative Module Content

Introduction to Research - This session will help you to start the wonderful journey of research. Research is useful for finding new opportunities ,  new discoveries and higher studies

Finding a research problem - Finding a research problem is the most important aspect of any research project . (Undergraduate, Postgraduate etc..)

Finalizing your objectives-

Research Methodology

Positivism

Interpretivism

Introduction to Machine Learning:-  What is  Machine Learning  ?, -> in this session we will get an overview of machine learning

Setting up the Environment for Machine Learning:-Downloading & setting-up Anaconda, Introduction to Google Collabs -

(All the instructions will be provided to setup the environment successfully.)

Artificial Neural networks [Theory and practical sessions - hands-on sessions] -  This practical hands-on session will guide you to create a comprehensive ANN project

Machine Learning Techniques : Support Vector Machines - Lecture & Hands - On  with Google Collabs ,

Trees and Random Forest - Lecture & Hands-On  with Google Collabs,



Course Content

  • 2 section(s)
  • 13 lecture(s)
  • Section 1 Introduction to Research
  • Section 2 Introduction to Machine Learning

What You’ll Learn

  • Introduction to Research
  • Finding a research problem
  • Finalzing your objectives
  • Research Methodology
  • Introduction to Machine Learning:-  What is  Machine Learning  ?,
  • Setting up the Environment for Machine Learning:-Downloading & setting-up Anaconda, Introduction to Google Collabs
  • Artificial Neural networks [Theory and practical sessions - hands-on sessions]
  • Support Vector Machines

Reviews

  • A
    Arshin Prabhakar T V
    4.5

    good

  • S
    Sourabh Kumar Das
    4.5

    very good

  • I
    Irshad Ali khan
    5.0

    Good course

  • A
    Akkaraju Sailesh Chandra
    5.0

    A very good start to Research in Machine Learning.

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