Machine Learning Techniques using Python

Model evaluation and optimisation, decision trees, random forests, logistic regression, SVMs, neural networks, deep learning and more.

LEVEL: INTERMEDIATE
DURATION: 3-DAY COURSE
DELIVERED: AT YOUR OFFICE

What you will learn

Python Machine Learning

You will learn advanced state-of-the art machine learning techniques that are in demand in industry and research.

Model evaluation and optimisation (grid search)
Decision trees and random forests
Logistic regression
SVMs (linear SVMs, kernel trick, nonlinear SVMs)
Neural networks
Deep learning (local and cloud-based)

Languages and libraries :

Python 3
Numpy and Pandas for data manipulation
Scikit-learn for machine learning algorithms
Keras for neural networks and deep learning

PREREQUISITES

Good knowledge of python, some familiarity with matrices, basic understanding of machine learning practice (as taught in Introduction to Data Science)

AUDIENCE

Individuals who wish to take their data science skills further and learn state-of-the-art techniques in this constantly evolving field.

Get in touch with us to learn more about the course! 

Get in Touch

DAY ONE

Random Forests, Logistic Regression, Support Vector Machines (SVMS)

DAY TWO

Neural Networks and Deep Learning

  • Neural Networks
    • Overview of modern applications of Neural Networks
    • The Perceptron
    • Structure of general neural networks
    • Training of Neural Networks
  • Deep Learning
    • Motivation and architecture
    • Real-world examples
    • Convolutional Neural Networks
    • Impact and limitations of Deep Learning

Get in Touch

CONTACT US

We will email you within the next 24 hours to arrange a quick call to help with any questions about the programme and recommend pre-course materials.

We look forward to speaking with you.

Dr. Raoul-Gabriel Urma

Dr. Raoul-Gabriel Urma

Director