Machine Learning Fundamentals with R Training Course

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Course Code

MLFWR1

Duration Duration

14 hours (usually 2 days including breaks)

Requirements Requirements

Knowledge of R programming language. Basic familiarity with statistics and linear algebra is recommended.

Overview Overview

The aim of this course is to provide a basic proficiency in applying Machine Learning methods in practice. Through the use of the R programming platform and its various libraries, and based on a multitude of practical examples this course teaches how to use the most important building blocks of Machine Learning, how to make data modeling decisions, interpret the outputs of the algorithms and validate the results.

Our goal is to give you the skills to understand and use the most fundamental tools from the Machine Learning toolbox confidently and avoid the common pitfalls of Data Sciences applications.

Course Outline Course Outline

Introduction to Applied Machine Learning

  • Statistical learning vs. Machine learning
  • Iteration and evaluation
  • Bias-Variance trade-off

Regression

  • Linear regression
  • Generalizations and Nonlinearity
  • Exercises

Classification

  • Bayesian refresher
  • Naive Bayes
  • Logistic regression
  • K-Nearest neighbors
  • Exercises

Cross-validation and Resampling

  • Cross-validation approaches
  • Bootstrap
  • Exercises

Unsupervised Learning

  • K-means clustering
  • Examples
  • Challenges of unsupervised learning and beyond K-means

Guaranteed to run even with a single delegate!
Public Classroom Public Classroom
Participants from multiple organisations. Topics usually cannot be customised
From 3900PLN
(89)
Private Classroom Private Classroom
Participants are from one organisation only. No external participants are allowed. Usually customised to a specific group, course topics are agreed between the client and the trainer.
Private Remote Private Remote
The instructor and the participants are in two different physical locations and communicate via the Internet
From 7000PLN
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The more delegates, the greater the savings per delegate. Table reflects price per delegate and is used for illustration purposes only, actual prices may differ.

Number of Delegates Public Classroom Private Remote
1 3900PLN 7000PLN
2 3450PLN 5000PLN
3 3300PLN 4333PLN
4 3225PLN 4000PLN
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Upcoming Courses

VenueCourse DateCourse Price [Remote / Classroom]
Olsztyn, ul. Kajki 3/1Mon, 2017-02-06 09:007000PLN / 4000PLN
Opole, Wladyslawa Reymonta 29Tue, 2017-02-07 09:007000PLN / 4400PLN
Gdynia, ul. Ejsmonda 2Thu, 2017-02-09 09:007000PLN / 4200PLN
Tarnów ul. Kościuszki 10 Thu, 2017-02-09 09:007000PLN / 4200PLN
Łódź, ul. Tatrzańska 11Mon, 2017-02-13 09:007000PLN / 4100PLN

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