Machine Learning Basics

Machine Learning Basics

  • 5.0 (2 Reviews) , 97 students enrolled

Course Overview

Machine learning is an application of artificial intelligence (AI) that provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it to learn for themselves. Machine Learning is the field of study that gives computers the capability to learn without being explicitly programmed. ML is one of the most exciting technologies that one would have ever come across. As it is evident from the name, it gives the computer that which makes it more similar to humans: The ability to learn. Machine learning is actively being used today, perhaps in many more places than one would expect.

What are the requirements?

  • Basic high-school level Mathematics.

What am I going to get from this course?

  • You will master in knowing which machine learning model to use for each type of problem.
  • You will learn to make accurate predictions and powerful analysis.
  • You will be able to personalise machine learning applications.

What is the target audience?

  • Anyone who is interested in learning Machine Learning.
  • Anyone who wishes to add value to their business using Machine Learning tools.

About the Author

We at SkillRary strive to provide simple yet powerful training or tuition on all domains. This organization has started with a mindset to share the knowledge that the internet or an individual has in a progressive manner. SkillRary is an online training programme, trying to get the best content for all on a very low cost and thereby helping everyone with a digital schooling and online education.  

SkillRary provides computer based training (CBT), distance learning or e-learning, that takes place completely on the internet. The courses involve a variety of multimedia elements, including graphics, audio, video, and web-links which can be accessed to the enrolled clients.

In addition to presenting course materials and content, SkillRary gives the students the opportunity for live interactions and real-time feedback in the form of quizzes and tests. Interactions between the instructor and students are also conducted via chat, e-mail or other web-based communication. Unlike any other, we here also let the students know which module has to be gone through first. All the modules are placed according to the lesson plans so that students will know what to refer first.

SkillRary is self-paced and customizable to suit an individual's specific learning needs. Therefore it can be conducted at any time and place, provided there is a computer or smartphone with high-speed internet access. This makes it very convenient to the users who can modify their training to fit into their day-to-day schedule. All our users will be able to use our eLearning system to its full capacity.

Course Curriculum

Table Of Content
1 Video Lectures | 00:03:52

  • Table of Content
    03:52
     

Machine Learning Introduction
4 Video Lectures | 00:55:08

  • Introduction
    16:18
     
  • Well posed learning problems
    09:20
     
  • Desgning a learning system
    25:13
     
  • issune in machine learning
    04:17
     

Concept Learning
10 Video Lectures | 01:35:11

  • Concept learning
    11:57
     
  • General to specific ordering of hypotheses
    09:28
     
  • Find a Algorithm
    14:16
     
  • Version Space
    03:49
     
  • list then eliminate algorithm
    10:56
     
  • candidate elimination algorithm
    09:01
     
  • candidate elimination algorithm example
    17:31
     
  • Remarks on Version Space
    08:34
     
  • unbiased learner
    02:12
     
  • Inductive learner
    07:27
     

Decision Tree Learning
12 Video Lectures | 02:15:29

  • Decision Tree
    06:23
     
  • Decision Tree Representation
    10:40
     
  • Problems for DTL
    10:20
     
  • Entropy
    07:25
     
  • Information Gain
    16:01
     
  • ID3
    08:29
     
  • IDE Example
    31:55
     
  • 2nd Exmple
    05:27
     
  • Some Insight of DL
    04:05
     
  • Inductive Bias of Dl
    06:41
     
  • Restriction Biases and Preference Biases
    05:49
     
  • Issues in Decision Tree
    22:14
     

reviews

  • Manu Kumar
    I found the course to be amazing. I got hands-on experience of implementation of machine learning.
    4 months ago
  • Suprit C
    The course was well structured, covering large concepts of ML. This course is a great start for anyone who is keen on learning ML.
    4 months ago