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This Machine Learning for Python Developers training course will provide you with an introduction to core Machine Learning techniques: you will get an overview of the Machine Learning landscape as well as tools and resources in Python.

 

Learning Objectives

  •     To have a familiarity with the Machine Learning landscape
  •     Understand the different types of Machine Learning algorithms
  •     Identify suitable Machine Learning techniques for different types of data
  •     To be understand how to implement and evaluate basic Machine Learning algorithms in Python

Machine Learning for Python Developers Training

Course Code

GTMLP

Duration

1 Day Lecture

Course Fee

POA

Accreditation

N/A

Target Audience

This is ideally suited for Python developers. No Machine Learning experience is required.

Attendee Requirements

Proficiency in Python development including: array manipulations with NumPy, loading libraries, and plotting using Matplotlib.


We are sorry, there is currently no availability on this course.

contact us for more information

Ways to Attend this Course

  • In the Classroom
  • Private Training

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Course Description

This Machine Learning for Python Developers training course will provide you with an introduction to core Machine Learning techniques: you will get an overview of the Machine Learning landscape as well as tools and resources in Python.

 

Learning Objectives

  •     To have a familiarity with the Machine Learning landscape
  •     Understand the different types of Machine Learning algorithms
  •     Identify suitable Machine Learning techniques for different types of data
  •     To be understand how to implement and evaluate basic Machine Learning algorithms in Python
Course Outline

Introduction

  •     A high level overview of key Machine Learning concepts

Topic 1

  •     Introduction to Regression: a supervised learning technique
  •     Regression analysis
  •     Regression demonstration

Topic 2

  •     Working with data
  •     Feature transformation introduction and demonstration
  •     Feature selection introduction and demonstration

Topic 3

  •     Introduction to clustering: an unsupervised learning technique
  •     Clustering demonstration

Topic 4

  •     Introduction to data classification
  •     Classifying data using Naïve Bayes demonstration

Topic 5

  •     Introduction to time-series analysis
  •     Time series analysis demonstration

Topic 6

  •     Introduction to Neural Networks
  •     Demonstration of Multilayer perceptrons
Ways to Attend
  • Attend a public course, check our schedule
  • Private onsite Team training also available

 

Sorry, we are not taking bookings on this course at present

If you would like to contact us for more information on this course, you may do so here:

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