Machine Learning Algorithms | Machine Learning Tutorial | Data Science Training | Edureka

This Machine Learning Algorithms Tutorial shall teach you what machine learning is, and the various ways in which you can use machine learning to solve a problem! Towards the end, you will learn how to prepare a data-set for model creation and validation and how you can create a model using any machine learning algorithm! In this Machine Learning Algorithms Tutorial video you will understand:

1) What is an Algorithm?
2) What is Machine Learning?
3) How is a problem solved using Machine Learning?
4) Types of Machine Learning
5) Machine Learning Algorithms
6) Demo

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#Edureka #MachineLearningAlgorithms #Datasciencetutorial #Datasciencecourse #datascience

How it Works?

1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project
2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
3. You will get Lifetime Access to the recordings in the LMS.
4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate!

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About the Course

Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities.

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Why Learn Data Science?

Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework.

After the completion of the Data Science course, you should be able to:
1. Gain insight into the 'Roles' played by a Data Scientist
2. Analyse Big Data using R, Hadoop and Machine Learning
3. Understand the Data Analysis Life Cycle
4. Work with different data formats like XML, CSV and SAS, SPSS, etc.
5. Learn tools and techniques for data transformation
6. Understand Data Mining techniques and their implementation
7. Analyse data using machine learning algorithms in R
8. Work with Hadoop Mappers and Reducers to analyze data
9. Implement various Machine Learning Algorithms in Apache Mahout
10. Gain insight into data visualization and optimization techniques
11. Explore the parallel processing feature in R

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Who should go for this course?

The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course:

1. Developers aspiring to be a 'Data Scientist'
2. Analytics Managers who are leading a team of analysts
3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics
4. Business Analysts who want to understand Machine Learning (ML) Techniques
5. Information Architects who want to gain expertise in Predictive Analytics
6. 'R' professionals who want to captivate and analyze Big Data
7. Hadoop Professionals who want to learn R and ML techniques
8. Analysts wanting to understand Data Science methodologies

Customer Reviews:

[purusothamanp]

Best Tutorial on Machine Learning at Beginner Level.

[drsheemu]

Best video ever for beginners... As I am one of them...

[balugoud]

Excellent and the last explanation for logistic regression and for classification was too good ..!!
Sure it will be fixed for life time
And we are expecting more videos on further algorithms.... thank you...!!

[soniadhamija]

Very good tutorial. Very well explained

[bhargs]

This s the best tutorial for Machine learning among all the videos I went through hats off guys..

[trknigatu]

This is an excellent video putting me close to understanding the ML. Big thanks!!!

[denniskamonde]

thanks edureka for the good work you are doing, to empower us with coding skills

[mfoncharles]

Nice and concise explanation. Can you please provide the data set you used, so we could also play around with it as practice. Thanks in anticipation

[rizolli-bxiv]

Reinforcement learning is applied in games

[achamyelehbirhanu]

Thank you Edureka for your nice presentation on an important topic!
I have one question, How can get the optimal cut of point for a continuous independent variable using a machine learning approach. could you give me a command?

[jaber]

Your videos are just awesome, clear and easy to understand . I really needed this video to get me through the Machine Learning dripline .I recommend every one who is interested to have a look in the following courses, they are great
1- Machine Learning Certification Training using Python
2- Python Certification Training for Data Science

[jothinathan]

Very useful, it will be more useful if can download this notes

[divyar]

Informative and clearly explained video:) thanks :)

[melwinalm]

You guys create amazing learning videos

[JustNavika.k]

The videos are really good. I was wondering where to start with the study on datasceience. And you just gave me a great start

[AnjumJaved]

Great session! Good explanation of ML concepts with hands on coding.

[pedurujagadish]

Sir please send machine learning course full syllabus