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Machine Learning for Data Science using R

Machine Learning offers clever alternatives in analysing huge volumes of data. It’s a hybrid of computer science and statistics and is being aggressively adopted in multifarious industry applications. Machine learning involves developing efficient and fast algorithms and data driven models for data processing. R-Programming is one of the preferred tools for Machine learning. We will develop a keen understanding and appreciation of Machine Learning Algorithms by doing in on R. Check out the learning objectives below .

Course Overview

Machine learning is one of the fastest growing areas of computer science with far reaching business applications. The aim of this course is to introduce you to machine learning, and the most widely used algorithms in business applications.

  • We would spend time learning how to apply different ML algorithms in practice datasets from various business situations
  • However, an important learning objective will be to develop an appreciation for the fundamental ideas of machine learning and the mathematical derivations that transform these ideas into practical algorithm.

R (Programming language) is free programming language and software environment for statistical computing, graphics and Machine Learning. The R language is widely used among data scientist, statisticians and data miners for developing data models and data analytics. R has become one the most sought-after skills in 2018.

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$250.0 / ₹ 17000.0 + GST

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WHAT YOU'LL LEARN / COURSE OBJECTIVE

  1. Introduction:
    1. What is learning?
    2. When you we need machine learning?
    3. Types of Machine learning?
  2. Foundations:
    1. The statistical learning framework.
    2. Risk – Problem of overfitting.
    3. Error decomposition.
  3. Theory to Algorithm
    1. Linear Regression
    2. Logistic Regression
    3. Multiclass ranking & complex prediction problems.
    4. Decision tree Algorithms (CART & Random Forest)
      1. Measures of Gain
      2. Pruning
      3. Splitting rules.
      4. Neural Networks.
      5. Nearest Neighbour.

Outline

Related Certifications

Not available.

PREREQUISITES

The course assumes that the student has no prior statistical or programming skills. However, comfort with college level math is must. Student need not know the math but should be comfortable with it.

Course Completion Certificate


Trainer Profile

Mithun Radhakrishnan, is a Freelance Data Enthusiast and Analyst.



He Primarily consults in the area of Digital Marketing. Mithun has consulted for multiple data projects as a Freelancer. Prior to this he was heading a team of stock analyst with a leading Bank in India.

In terms of Qualification, he has PG in Business Analytics and Business Intelligence from Illinois Institute of Technology. He is also a Chartered Market Technician (CMT) which is the highest certification in the field of Technical Analysis of stock market data. He also has ......

Subject-matter expert

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Any Technical Queries?

Our Trainers always ready to take your questions related to learning subject and resolve them to the best of thier capablities. You can connect with them either on Skype, email or in special cases call them on Phone or WhatsApp.

 
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