Your new post is loading...
Take a tour of the most popular machine learning algorithms.
Other Lists of Algorithms
There are other great lists of algorithms out there if you’re interested. Below are few hand selected examples.
- List of Machine Learning Algorithms: On Wikipedia. Although extensive, I do not find this list or the organization of the algorithms particularly useful.
- Machine Learning Algorithms Category: Also on Wikipedia, slightly more useful than Wikipedias great list above. It organizes algorithms alphabetically.
- CRAN Task View: Machine Learning & Statistical Learning: A list of all the packages and all the algorithms supported by each machine learning package in R. Gives you a grounded feeling of what’s out there and what people are using for analysis day-to-day.
- Top 10 Algorithms in Data Mining: Published article and now a book (Affiliate Link) on the most popular algorithms for data mining. Another grounded and less overwhelming take on methods that you could go off and learn deeply.
How to Study Machine Learning Algorithms
Algorithms are a big part of machine learning. It’s a topic I am passionate about and write about a lot on this blog. Below are few hand selected posts that might interest you for further reading.
- How to Learn Any Machine Learning Algorithm: A systematic approach that you can use to study and understand any machine learning algorithm using “algorithm description templates” (I used this approach to write my first book).
- How to Create Targeted Lists of Machine Learning Algorithms: How you can create your own systematic lists of machine learning algorithms to jump start work on your next machine learning problem.
- How to Research a Machine Learning Algorithm: A systematic approach that you can use to research machine learning algorithms (works great in collaboration with the template approach listed above).
- How to Investigate Machine Learning Algorithm Behavior: A methodology you can use to understand how machine learning algorithms work by creating and executing very small studies into their behaviour. Research is not just for academics!
- How to Implement a Machine Learning Algorithm: A process and tips and tricks for implementing machine learning algorithms from scratch.
How to Run Machine Learning Algorithms
Sometimes you just want to dive into code. Below are some links you can use to run machine learning algorithms, code them up using standard libraries or implement them from scratch.
- How To Get Started With Machine Learning Algorithms in R: Links to a large number of code examples on this site demonstrating machine learning algorithms in R.
- Machine Learning Algorithm Recipes in scikit-learn: A collection of Python code examples demonstrating how to create predictive models using scikit-learn.
- How to Run Your First Classifier in Weka: A tutorial for running your very first classifier in Weka (no coding required!).
