What Azure Machine Learning Algorithm Should You Use

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Azure Machine Learning Studio comes with a large number of machine learning algorithms that you can use to solve predictive analytics problems. The infographic below demonstrates how the four types of machine learning algorithms – regression, anomaly detection, clustering, and classification – can be used to answer your machine learning questions. The Microsoft Azure Machine Learning Algorithm Cheat Sheet helps you choose the right machine learning algorithm for your predictive analytics solutions from the Microsoft Azure Machine Learning library of algorithms. To download the cheat sheet and follow along with this article, go to Machine learning algorithm cheat sheet for Microsoft Azure Machine Learning Studio. This cheat sheet is perfect for students its aimed at someone with undergraduate-level machine learning, trying to choose an algorithm to start with in Azure Machine Learning Studio.


Selecting a right Machine Learning algorithm for predictive analytics needs: Classification vs Regression vs Clustering - Big Data Analytics Guide

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An interesting cheat sheet (a nice infographic!) was published by Microsoft sometime back to help beginning data scientists on how to choose a Machine Learning algorithm for different predictive analytics needs: Classification (to predict categories), Clustering (to discover structure), Regression (to predict values) and Anomaly Detection (to find unusual data points). Here's what Brandon, the author of the article "How to choose algorithms for Microsoft Azure Machine Learning", says about it: "It depends on the size, quality, and nature of the data. It depends what you want to do with the answer. It depends on how the math of the algorithm was translated into instructions for the computer you are using. And it depends on how much time you have.


How to Get Data Science and Machine Learning/AI Jobs How to Become a Data Scientist

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At present, the majority of machine learning jobs involve working with large datasets. You can't do that using a single machine. So, you need to distribute across a cluster. Get acquainted with tools like Apache Hadoop, and cloud services like Rackspace, Amazon EC2, Google Cloud Platform, OpenStack, and Microsoft Azure etc. You should also master all of the great Unix tools such as cat, grep, find, awk, sed, sort, cut, tr etc. Since all of the processing will most likely be the on the Linux-based machine, you need access to learn these tools, their functions, and applications.


Cheat Sheet of Machine Learning and Python (and Math) Cheat Sheets

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If you really want to understand Machine Learning, you need a solid understanding of Statistics (especially Probability), Linear Algebra, and some Calculus. I minored in Math during undergrad, but I definitely needed a refresher. These cheat sheets provide most of what you need to understand the Math behind the most common Machine Learning algorithms.


Cheat Sheet of Machine Learning and Python (and Math) Cheat Sheets

@machinelearnbot

If you really want to understand Machine Learning, you need a solid understanding of Statistics (especially Probability), Linear Algebra, and some Calculus. I minored in Math during undergrad, but I definitely needed a refresher. These cheat sheets provide most of what you need to understand the Math behind the most common Machine Learning algorithms.