Machine Learning with C – Learn the machine with C ++ Plus
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.
Table of Contents:
– 1 The Purposes of Machine Learning
– 2 Modeling a Problem with Linear Regression
– 3 Cluster Analysis with K-Means
Producer: Tom Joy
Teacher: Phil Culliton
Level of training: Preliminary
time of training: 1 hour + 30 minutes
File size: 232 MB