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A Pragmatic Approach to Machine Learning with R for 2021

 

A Pragmatic Approach to Machine Learning with R for 2021

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A Pragmatic Approach to Machine Learning with R for 2021 No experience needed. Learn by doing. Start for Free. Learn from a full time machine learning gig consultant.

What you'll learn

  • How to apply methodology to assure the success of machine learning projects.
  • How to comfortably replace Excel with R, never returning to Excel for analysis again!
  •     How to import, shape, mould, filter, arrange and aggregate date in R instead of using a database for the same.
  • How to make assertions about data with summary statistics and make one variable predictions.
  • How to express domain experience given data and the overarching importance of Abstraction.
  • How to make classifications with Logistic Regression, C5 Decision Trees and Neural Networks.
  • How to make numeric predictions with Linear Regression, Regression Trees and Neural Networks.
  • How to make pragmatic use of visualisations.
  • How to use subjective probability and know its function in Bayesian networks.
  • How to use Monte Carlo simulation with numeric predictions or classifications for the purposes of optimisation.
  • How to integrate models as high performance HTTP microservices.

Requirements

  • Interest and curiosity about machine learning.
  • A project to move onto immediately on conclusion of the course to avoid skill fade.

Description

  • Data drives everything and machine learning is fast becoming the bedrock of all business processes.  The future or work belongs to those who can create machine learning, not to those that simply use its output. There is a shortfall of individuals who can create machine learning. Get the skills you need for the future of work.
  • This training course presents machine learning in real business environments, cutting through the traditional academic applications to get to valuable business outcomes instead.

The course came about in a biographical fashion with the trainer documenting slides and procedures for the purposes of reducing his own skill fade after each machine learning consulting gig.  Over time it grew to the following resources (which are published alongside the free modules):

  • Full training data used throughout the course.
  • The full PDF book of training procedures.

R has become the standard for machine learning. The cost efficiency of R – it is free – coupled with the incredible variety of supplementary packages available to augment its powerful command-based interface, makes it a one stop shop. It is little wonder that it is unseating commercial rivals as the corporate choice. When taken together with the wide array of packages available to R, nearly anything required of an individual practicing machine learning, is available in R, and therefore, without any cost.

This course will develop your skills in data analysis, summary statistics, as well as machine learning using regression, probability, decision trees, Na├»ve Bayesian networks and Neural Networks. 

  A Pragmatic Approach to Machine Learning with R for 2021 | Udemy

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