Machine learning as we all know, provides computers the ability to learn and adapt changes and make decisions without being explicitly programmed. The process of machine learning is similar to that of data mining has evolved from the study of pattern recognition and computational learning theory in artificial intelligence.
The machine learning algorithms can be categorized as being supervised or unsupervised. The supervised algorithms can apply what has been learned in the past to new data, on the other hand, unsupervised algorithms draw inferences from datasets.
For example, Facebook’s News Feed uses machine learning to customize each user’s feed. If a user regularly stops scrolling in order to read, like or share a specific friend’s post, next time, the News Feed will start showing more of that friend’s activity earlier in the feed. In the backend, the program is using statistical and predictive analysis to examine and identify patterns in the user’s data. If the user no longer stops to read on the friend’s post, the new datasets will be included and News feed will adjust accordingly.
We’ve gathered a list of some useful machine learning cheat sheets that will help you to gain insight knowledge on artificial intelligence.
16. Scikit-Learn Algorithm Cheat Sheet
Sometimes the hardest part of solving a machine learning problem can be searching the optimal estimator for the job. Different estimators are required to solve different problems. The flowchart is designed to give users a rough guide on how to approach problems with regard to which estimator you should implement on data.
15. Machine Learning Algorithms and Commands
Created by Ajitesh Kumar, this sheet contains 10 famous machine learning algorithms and related R commands along with package information. The aim is to represent a quick reference page for beginners who are working on machine learning related issues.
14. Understanding Machine Learning: For Beginners
Created by Todd Jaquith, this infographic is perfect for beginners. It simply explains, what machine learning is, what’s the history, how it is implemented, what are the approaches and applications.
13. Machine Learning Algorithms Mindmap
Getting started with machine learning can be enervating and searching the right algorithm or technique could be deceptive. This mindmap will give you a baseline to select the right machine learning algorithm for your requirements.
12. Python and R codes
The collection of 10 most commonly used machine learning algorithms with their codes in Python and R. Both these programming languages make the task easier than more people realize because both come with various built-in and extended support, through the use of datasets, libraries and other resources.
11. Cheat Sheet for Dummies
The cheat sheet has two parts, both are created in table structure. The first one gives you a quick summary of the weakness and strengths of different machine learning algorithms. The second table provides you the list of libraries used for both Python and R. When you want to implement any algorithm-related task, simply load the library needed for that task into your source code.
10. Machine Learning Systems for SEO
The United Kingdom based management and search optimization agency Alchemy Viral created an in-depth infographics on machine learning systems and how it factors in to SEO (Search Engine Optimization) tactics.
9. Top Machine Learning Algorithms
In order to address the complex nature of various real world data problems, specialized algorithms have been created to solve these problems in less time using less resources. For beginners, this is a brief discussion on the top machine learning algorithms used by data scientists.
8. Algorithm for Supervised and Unsupervised Learning
In order to summarize the most important material, Emanuel Ferm created a cheat sheet in LaTeX. It includes learning and applying linear classifiers and clustering algorithms on smaller data sets.
7. Supervised Learning Superstitions Cheat Sheet
This one is created by Ryan Compton, and contains several commonly used supervised learning algorithms. Different methods have been discussed, including logistic regression, decision trees, K nearest neighbors, Naive Bayes and support vector machines.
6. How Machine Learning Works in Mobile Messaging?
The infographic by kahuna shows you how do companies use machine learning technology to deliver a better customer experience.
5. Machine Learning: Equations and Algorithms
A simple machine learning cheat sheet made by Dr. Rico Möckel. It includes various equations and algorithms along with their description.
4. Machine Learning Cheat Sheet
This is a detailed cheat sheet that contains a wide range of classical equations and diagrams, which will help you quickly recall knowledge on machine learning. Not only for developers, it also comes handy if you are preparing for a job interview related to artificial intelligence.
3. Machine Learning in Emoji
Emily Barry mixed the machine learning algorithm with her emoji love. As a result, she came up with a comprehensive and eye catching guide to machine learning that is fun to read.
2. Machine Learning: Pattern for Predictive Analytics
Another helpful machine learning cheat sheet coming form Dzone that covers predictive analytics, explains setting up training and testing data, and offers machine learning model snippets.
1. Microsoft Azure Machine Learning
The Microsoft Azure Machine Learning will help you select the appropriate algorithm for a predictive analytics model. The Azure Studio has a wide range of algorithms from the regression, clustering, classification and anomaly detection families. Each one is developed to address different type of machine learning problem.