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This Machine Learning for Python Developers training course is a hands-on introduction to core Machine Learning techniques. This course will familiarise you with the Machine Learning landscape as well as providing practical experience.

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 able to implement and evaluate basic Machine Learning algorithms using Python libraries

 

 

Machine Learning for Python Developers Training

Course Code

GTMLP1

Duration

2 Days Practical

Course Fee

POA

Accreditation

N/A

Target Audience

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

Attendee Requirements

Those attending this training course require a proficiency in Python development including: array manipulations with NumPy, loading libraries, and plotting using Matplotlib.

Course set-up

  •     Laptop with the latest version of Python and
  •     A suitable IDE (PyCharm)
  •     Anaconda 3 interpreter
  •     TensorFlow 1.0

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

contact us for more information

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Course Description

This Machine Learning for Python Developers training course is a hands-on introduction to core Machine Learning techniques. This course will familiarise you with the Machine Learning landscape as well as providing practical experience.

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 able to implement and evaluate basic Machine Learning algorithms using Python libraries

 

 

Course Outline

Day 1: The Machine Learning Landscape

Introduction

  •     A high level overview of key Machine Learning concepts
  •     Overview of Machine Learning tools and resources for Python

Topic 1

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

Topic 2

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

Topic 3

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

Topic 4

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

Topic 5

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

Day 2: Neural Networks with TensorFlow

Introduction

  •     Introduction to Neural Networks
  •     Introduction to TensorFlow
  •     Demonstration

Topic 1

  •     A simple network: lab
  •     Tuning and hyperparameters

Topic 2  

  •     More complex network labs:

                          Image recognition
                          Recurrent Neural Networks

 

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

However, this course may be available as a private team training course. If you would like to contact us for more information on this course, you may do so here:

Private Team Training | Contact us

Technical ICT learning & mentoring services

Private Team Training

Our instructors are specialist consultants with vast real world experience and expertise allowing them to design and deliver client-focused courses for your organisation.

Learn more about our Private Team Training

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“Very interesting course from an excellent instructor. Highly technical and well delivered”

 

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