Machine Learning Algorithms

A curated 2026 directory of 17 verified resources for machine learning algorithms, spanning supervised, unsupervised, and ensemble methods.

• A Tour of Machine Learning Algorithms by Jason Brownlee

  A comprehensive tour through the main classes of machine learning algorithms, grouped by learning style and by function.

• Machine Learning Algorithms for Beginners

  An accessible rundown of the machine learning algorithms every data science beginner should know.

• Machine Learning Algorithms by Upasana

  A practical walkthrough of the most widely used machine learning algorithms and how they fit into the ML workflow.

• The Top Ten ML Algorithms Every Beginner Has to Know by James Le

  A beginner-friendly tour of the ten machine learning algorithms most commonly used by data scientists.

• Top Machine Learning Algorithms Used by Data Scientists

  An in-depth look at the top algorithms data scientists rely on, with explanations of how each one works.

• The Growing List of Machine Learning Algorithms

  A continually updated catalog of machine learning algorithms spanning supervised, unsupervised, and ensemble methods.

• Explaining Machine Learning Algorithms in Detail by GeeksforGeeks

  A detailed reference covering the theory and implementation of core machine learning algorithms.

• A Perspective on Machine Learning Algorithms by Martin Heller

  An InfoWorld deep dive explaining the algorithms that power modern AI and machine learning systems.

• Focusing on the Top Ten Machine Learning Algorithms

  A rundown of the ten machine learning algorithms every engineer should know, with real-world applications for each.

• A Blog on the Four Types of ML Algorithms by Oleksandr Bushkovskyi

  An overview of the four major types of machine learning algorithms: supervised, unsupervised, semi-supervised, and reinforcement.

• Comparing Different Supervised Machine Learning Algorithms for Disease Prediction

  A peer-reviewed BMC study comparing the performance of supervised machine learning algorithms across disease prediction research.

• An Introductory Primer on Machine Learning Algorithms by Nick McCrea

  A visual, example-driven primer from Toptal covering the theory behind supervised and unsupervised machine learning.

• The Classification of Machine Learning Algorithms for Beginners

  A structured overview of how machine learning algorithms are classified by learning style and task.

• A Blog on Top Machine Learning Algorithms & How To Get Started

  A BMC guide walking through popular machine learning algorithms and the tools needed to get started.

• 9 Key Machine Learning Algorithms Explained in Plain English by Nick McCullum

  A no-code introduction to nine of the most important machine learning algorithms, explained in plain English.

• A Gentle Introduction to Machine Learning Algorithms

  A beginner's guide covering supervised, unsupervised, semi-supervised, and reinforcement learning algorithms with real-world examples.

• Modern Machine Learning Algorithms: Strengths and Weaknesses

  A practical, concise tour of modern machine learning algorithms organized by task, with the tradeoffs of each.