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Brought to you by QCIF in partnership with Intersect and delivered by Intersect eResearch Analysts and trainers, this workshop will give you an comprehensive introduction to machine learning, one of the most exciting techniques in computational data analysis.

Machine Learning (ML) is a new way to program computers to solve real world problems. It has gained popularity over the last few years by achieving tremendous success in tasks that we believed only humans could solve, from recognising images to self-driving cars. In this course, we will explore the fundamentals of Machine Learning from a practical perspective with the help of the Python programming language and its scientific computing libraries.

We will explain the fundamentals of Machine Learning and provide a comprehensive introduction to Linear Regression and Model Training, and will use Python to apply this knowledge to real-world datasets. After this hands-on workshop, you will have a better understanding of these Machine Learning models and techniques and be able to make better informed decisions on how to leverage Machine Learning in your research.

Recommended Participants

Attendees must have a good knowledge of the basic concepts and techniques of Python – attendance at one of QCIF’s Software Carpentry “Introduction to Programming with Python” workshops is suitable background.

Learning Objectives

  • Understand the difference between supervised and unsupervised Machine Learning.
  • Understand the fundamentals of Machine Learning.
  • Comprehensive introduction to Machine Learning models and techniques such as Linear Regression and Model Training.
  • Understand the Machine Learning modelling workflows.
  • Use Python and scikit-learn to process real datasets, train and apply Machine Learning models

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