Machine Learning

Use Random Forest: Testing 179 Classifiers on 121 Datasets

Last Updated on July 31, 2020 If you don’t know what algorithm to use on your problem, try a few. Alternatively, you could just try Random Forest and maybe a Gaussian SVM. In a recent study these two algorithms were demonstrated to be the most effective when raced against nearly 200 other algorithms averaged over more than 100 data sets. In this post we will review this study and consider some implications for testing algorithms on our own applied machine […]

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Machine Learning

Practical Machine Learning Books for the Holidays

Last Updated on August 16, 2020 O’Reilly books have a reputation for being practical, hands on and useful. Specifically the nutshell books and so-called animal books. O’Reilly have a few new books out in time for the holidays on the topic of machine learning. I don’t want to bore you with reviews, Amazon has plenty of those. In this post we take a quick look at these new machine learning books and see what might be worth reading in the holiday […]

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Machine Learning

How To Get Started In Machine Learning: A Self-Study Blueprint

Last Updated on June 7, 2016 How do you get started in machine learning, specifically Deep Learning? This question was asked recently in the machine learning sub-reddit. Specifically, the original poster of the question had completed the Coursera Machine Learning course but felt like they did not have enough of a background to get started in Deep Learning. I wrote a lengthy reply that I think may be helpful more generally, for other people in the same situation that are […]

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Machine Learning

How To Work Through A Problem Like A Data Scientist

Last Updated on August 15, 2020 In a 2010 post Hilary Mason and Chris Wiggins described the OSEMN process as a taxonomy of tasks that a data scientist should feel comfortable working on. The title of the post was “A Taxonomy of Data Science” on the now defunct dataists blog. This process has also been used as the structure of a recent book, specifically “Data Science at the Command Line: Facing the Future with Time-Tested Tools” by Jeroen Janssens published […]

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Machine Learning

Machine Learning With Statistical And Causal Methods

Last Updated on September 5, 2016 In November 2014, Bernhard Scholkopf was awarded the Milner Award by the Royal Society for his contributions to machine learning. In accepting the award, he gave a layman’s presentation of his work on statistical and causal machine learning methods titled “Statistical and causal approaches to machine learning“. It’s an excellent one hour talk and I highly recommend that you watch it. Statistical Learning On the statistical side, Scholkopf talks about empirical inference and generalisation. An interesting and motivating point he makes early […]

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Machine Learning

Linear Algebra for Machine Learning

Last Updated on August 15, 2020 You do not need to learn linear algebra before you get started in machine learning, but at some time you may wish to dive deeper. In fact, if there was one area of mathematics I would suggest improving before the others, it would be linear algebra. It will give you the tools to help you with the other areas of mathematics required to understand and build better intuitions for machine learning algorithms. In this […]

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Machine Learning

Common Pitfalls In Machine Learning Projects

Last Updated on June 7, 2016 In a recent presentation, Ben Hamner described the common pitfalls in machine learning projects he and his colleagues have observed during competitions on Kaggle. The talk was titled “Machine Learning Gremlins” and was presented in February 2014 at Strata. In this post we take a look at the pitfalls from Ben’s talk, what they look like and how to avoid them. Machine Learning Process Early in the talk, Ben presented a snap-shot of the process for working […]

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Machine Learning

What To Do During Machine Learning Model Runs

Last Updated on June 7, 2016 There was a recent question that asked “How to not waste-time/procrastinate while ml scripts are running?“. I think this is an important question. I think answers to this question show a level of organization or maturity in your approach to work. I left a small comment on this question, but in this post I elaborate on my answer and give you a few perspectives on how to consider this question, minimize it and even […]

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Machine Learning

Get Started and Make Progress in Machine Learning

Last Updated on June 7, 2016 In this post I layout my manifesto for how you can get started and make progress in machine learning. In this post you will discover what machine learning is, why it matters, how to do it and how to identify and overcome your self-limiting beliefs. Get Started and Make Progress in Machine LearningPhoto by Sam Howzit, some rights reserved Why Get Started in Machine Learning I believe machine learning is an important and fascinating field. You can […]

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Machine Learning

Get Paid To Apply Machine Learning

Last Updated on September 27, 2016 The Ladder Approach That You Can Use To Become aMachine Learning Consultant Do you want to do machine learning and get paid for it? Be careful what you wish for. In this post I outline a blueprint that you can use to learn enough machine learning to help small businesses and start-ups with their general data needs. It’s not easy, you will have to work hard outside of your comfort zone. You will have […]

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