Machine Learning with C++ [Video]

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Machine Learning with C++ [Video]

Tom Joy

Up your algorithm building game by using C++ to predict and cluster data.
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Video Details

ISBN 139781788477727
Course Length1 hour and 29 minutes

Video Description

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.

Table of Contents

The Purposes of Machine Learning
The Course Overview
Why Do We Use ML?
Variety of Data Types
Variety of ML Algorithms
Simple Classification Task
Why Choose C++?
Modeling a Problem with Linear Regression
A Brief Overview of Linear Regression
Implementing Linear Regression
Implementing the trainAlgorithm Member Function
Implementing the Regress Function
Implementing Linear Regression Using a while Loop
Adjusting the Step Size
Discussion
Cluster Analysis with K-Means
What Is Clustering?
Implementing the K-Means Algorithm
Implementing the clusterData Function
Implementing computeMeans Function
Implementing the assignLabels Function
Implementing the printClusters Function
Choosing K
Discussion

What You Will Learn

  • Start your Machine Learning journey with C++
  • Understand the difference between generative and discriminative Machine Learning.
  • Understand the difference between unsupervised and supervised learning.
  • Explore the benefits of Linear Regression and Logistic Regression.
  • Implement a Linear Regression algorithm.
  • Understand the difference between K-means and K-NN.
  • Implement a K-means algorithm.

Authors

Table of Contents

The Purposes of Machine Learning
The Course Overview
Why Do We Use ML?
Variety of Data Types
Variety of ML Algorithms
Simple Classification Task
Why Choose C++?
Modeling a Problem with Linear Regression
A Brief Overview of Linear Regression
Implementing Linear Regression
Implementing the trainAlgorithm Member Function
Implementing the Regress Function
Implementing Linear Regression Using a while Loop
Adjusting the Step Size
Discussion
Cluster Analysis with K-Means
What Is Clustering?
Implementing the K-Means Algorithm
Implementing the clusterData Function
Implementing computeMeans Function
Implementing the assignLabels Function
Implementing the printClusters Function
Choosing K
Discussion

Video Details

ISBN 139781788477727
Course Length1 hour and 29 minutes
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