ML has become a fundamental part of the 21st century; from Netflix recommendations to fraud detection, ML is ever- present in our daily lives. At its roots, ML effectively applies statistics and pattern recognition, we will use these ideas to help solve a range of modern-day problems. C++ is a very fast language to execute your code and is extensively used when your final "models" are being deployed. If you want to run a program, with a lot of array calculation then C++ should be your weapon of choice. This course will start off with a broad overview of ML and the varying methods associated with it. You will understand data types, Machine Learning algorithms, and a simple classification task. We then study two simple but effective algorithms to deepen your understanding and provide some practical experience. Specifically, the two algorithms that we will be investigating are linear regression and K-means clustering. By taking this course, you will be able to get your machine Learning basics right and be able to build efficient algorithms which will help you to predict and cluster data. Style and Approach: This course takes you through the fundamentals of Machine Learning, and how you can utilize your C++ skills to build efficient algorithms for predicting and clustering data.
Target Audience
This course is designed for, and targeted at students who are competent in basic statistics and mathematical techniques and are looking for an introduction to machine learning. This course will provide a concrete foundation for future progression. We will be programming in C++, and hence some experience, and understanding of OOP is required. We will not be implementing any advance C++ code but familiarity with the language will be a strong advantage.
Business Outcomes
- An introduction to Machine Learning with C++.
- Understand linear regression and its benefits and pitfalls.
- Understand K-means clustering and its benefits and pitfalls.
