Implementing AI Algorithms from Scratch in C++ (Part 1)

Overview

What you'll learn

• Implement simple and multiple linear regression in C++
• Build logistic regression using gradient descent
• Construct k-nearest neighbors, Naive Bayes, and decision tree classifiers
• Implement stochastic and mini-batch gradient descent
• Apply Momentum, RMSProp, and Adam optimization methods
• Calculate classification metrics, including confusion matrix, precision, recall, and AUC-ROC
• Evaluate and compare machine learning model performance

Advantages and disadvantages

Some points apply to every course of this kind; see how we rank.

Before you start

Intermediate: Coding and Data Algorithms (C++) Intermediate: Machine Learning Model Development (C++)