The goal of machine learning is to program computers to use example data or past experience to solve a given problem.
This course provides an introduction to machine learning i.e. how to make computers learn from data. Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine
learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. In this class, you will learn about the most effective machine learning
techniques, and gain practice implementing them and getting them to work for yourself.
More importantly, you'll learn about the theoretical underpinnings of machine learning, gaining the practical know-how needed to quickly and powerfully apply techniques to new problems.
You'll also learn about some of Silicon Valley's best practices in innovation as it pertains to ML and AI(Artificial Intelligence).
Topics include statistics, linear algebra, supervised learning (regression and classification, parametric/non-parametric learning, neural networks, and support vector machines); unsupervised learning (clustering, dimensionality
reduction); model optimization and learning theory(bias/variance trade-offs). The course will also discuss recent advances such as deep learning, convolutional neural networks, and large scale machine learning.
PKR 60,000 per intake
Please contact or visit us if you need more information.