Introduction to Machine Learning

ML is a day-to-day life application of AI. As technology evolves, we need to get acquainted with it. This presentation gives us a brief introduction, methods and applications of ML.

Transcript

1. INTRODUCTION TO MACHINE LEARNING By: Damilola Omoyiwola Android Developer | Co-founder, Budgetier
4. What is Machine Learning? • A branch of AI based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
5. What is Machine Learning? • “Machine Learning is the field of study that gives computers the ability to learn without being explicitly programmed.” - Arthur Samuel, 1959
6. What is Machine Learning? • “A computer program is said to learn from experience E with respect to some task T and some performance measure P, if its performance on T, as measured by P, improves with experience E.” - Tom Mitchell, 1997.
7. Why Machine Learning? • It solves problems that cannot be solved by numerical means alone. • It aids in filtering useful pieces of information that help in major advancements.
8. Methods of Machine Learning
9. Applications of Machine Learning Virtual Personal Assistants
10. Applications of Machine Learning Predictions while Commuting (Traffic Predictions and Online Transportation Networks)
11. Applications of Machine Learning Social Media Services (Face Recognition, people you may know and similar pins)
12. Applications of Machine Learning Videos Surveillance
13. Applications of Machine Learning Others: • Email Spam and Malware Filtering • Online Customer Support • Search Engine Result Refining • Product Recommendations • Online Fraud Detection
15. “The goal of machine learning is to create a system that solves a specific problem.”
16. Thank You Twitter: @princessdharmy, @budgetier