In this post, you will get to look at some of the great mind-maps for learning different machine learning topics. I have gathered these mind maps from different web pages on the Internet. The idea is to reinforce our understanding of different machine learning topics using pictures. You may have heard the proverb – A picture is worth a thousand words. Keeping this in mind, I thought to pull some of the great mind maps posted on different web pages. I would be updating this blog post from time-to-time. If you are a beginner data scientist or an experienced one, you may want to bookmark this page for refreshing your machine learning concepts from time-to-time.
The first one is a great mind map to understand the usage of different classical machine learning algorithms with examples.
Here is another one. It highlights different types of machine learning algorithms vis-a-vis real-world applications. Three types of machine learning algorithms shows represent supervised learning, unsupervised learning, and reinforcement learning.
Here is another mind map representing an approach to solving real-world problems using machine learning. This one can be found on Sklearn page – Choosing the right estimator. You may note that it all starts with the data. Thus, before starting on with a machine learning-based solution, you may want to ensure that you have a decent volume of data.
Here is another one representing machine learning algorithm types and associated machine learning algorithms. You may note that it depicts one type of algorithm such as ensemble learning. Actually, ensemble learning algorithms can be used to solve regression and classification problems. Another type of machine learning algorithm is deep learning. Again, these kinds of algorithms can be used to solve both regression and classification problems.
Here is another one with a great representation of reinforcement learning. This is taken from the Louis Kirsch page. There are some great posts on different machine learning topics on this website. It does talk about four different methods used in reinforcement learning.
- Value-based learning
- Policy-based learning
- Imitation learning
- Model-based learning
Here is a good one showing different techniques that could be used for model evaluation. The details could be found on this model evaluation page by Dr. Sebastian Raschka
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