Machine Learning
Using Python Application

Introduction

The purpose of the webinar is to let the students enter the machine learning world and let them build their first Predicting Model. Machine Learning is the core of artificial intelligence. is programming computers to optimize a performance criterion using example data or past experience.

Machine learning has been used in several places like the self-driving Google car, the online recommendation engines – friend recommendations on Facebook, offer suggestions from Amazon, and in cyber fraud detection.

Objectives

• • Setting up the machine learning environment.
• • Exploring types of machine learning.
• • Using scikit-learn for machine learning.
• • Building your first predicting model.

Contents

• • What is Machine Learning.
• • Downloading and installing Anaconda.
• • Introduction to Jupyter notebook.



Types of machine learning.

• • Supervised learning.
• • Unsupervised learning.
• • Reinforcement learning.



Using scikit-learn for machine learning.

• • What is scikit-learn.
• • Data representation in scikit-learn.
• • Estimator API.
• • Building your first predicting model.

About the Facilitator

Lucine Gharibian is a teaching professional offering over 12 years of work experience as a teacher at universities and computer centers in UAE and abroad. Currently working as teacher at MSc. BigData, BSc Software Engineering and BSc Computing Science in Department of Computing, University of Stirling, RAK campus, UAE. During her career she taught many courses for UG and PG students and she was second marker for many of master’s dissertation projects.