Machine Learning using R Training - Live Virtual Classroom
Zeolearn
Summary
- Tutor is available to students
Overview
If you want to make a career in predictive analysis or work with big data then you have to understand machine learning and R is the most popular platform for applied machine learning. This open source programming language is among the most widely used languages for statistics and data mining, gives quick results and is supported by a worldwide community of users and developers.
Zeolearn academy’s comprehensive Machine Learning using R course is a must for those who see themselves as future analysts. The aim of this course is to familiarise you with statistical models for supervised and unsupervised learning using R programming language and how the R language environment supports predictive modelling with machine learning. Enrol now for a complete hands on familiarity on Machine Learning in R.
Description
Here’s what you will learn!
- How general predictive modeling and unsupervised learning are implemented in R
- How data is classified using classification algorithms and clustering in R
- The concept of regression, forecasting and visualizing the time series data
- Important models such as tree based, support vector machines and other fundamentals
Module 1: Introduction
- What is machine learning
- Explanation and prediction
- Learning system model
- Terminology
- Training and testing
- Performance
- Algorithms
- Structure
Module 2: Tools
Module 3: Correlation and Regression
Module 4: The Loss Function
Module 5: Regularisation
Module 6: Bias-Variance Tradeoff
Module 7: Cross-Validation
Module 8: Model Assessment & Selection
Module 9: Process Overview
Module 10: Opening the Black Box
Module 11: Other
Module 12: Naive Bayes classification
Module 13: Decision Trees
Module 14: Summary
Who is this course for?
Statisticians, Data Analysts, Business Analysts and professionals keen to learn more about the science and practice of Machine Learning using R, will benefit from this course.
Requirements
- Basic knowledge of a programming language such as Python or Java
- A background in Mathematics will be beneficial
System Requirements
- Operating system such as Mac OS X, Windows or Linux
- Good Text / JavaScript Editor (Notepad++ / SublimeText / Brackets / Atom )
- A modern web browser such as Chrome
- High speed Internet Connection
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Legal information
This course is advertised on reed.co.uk by the Course Provider, whose terms and conditions apply. Purchases are made directly from the Course Provider, and as such, content and materials are supplied by the Course Provider directly. Reed is acting as agent and not reseller in relation to this course. Reed's only responsibility is to facilitate your payment for the course. It is your responsibility to review and agree to the Course Provider's terms and conditions and satisfy yourself as to the suitability of the course you intend to purchase. Reed will not have any responsibility for the content of the course and/or associated materials.
