5 Machine Learning Areas You Should Be Cultivating

Last Updated on June 7, 2016 You want to learn machine learning to have more opportunities at work or to get a job. You may already be working as a data scientist or machine learning engineer and looking to improve your skills. It is about as easy to pigeonhole machine learning skills as it is programming skills (you can’t). There is a wide array of tasks that require some skill in data mining and machine learning in business from data […]

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How to Study Machine Learning Algorithms

Last Updated on August 12, 2019 Algorithms make up a big part of machine learning. You select and apply machine learning algorithms to build a model from your data, select features, combine the predictions from multiple models and even evaluate the capabilities of a given model. In this post you will review 5 different approaches that you can use to study machine learning algorithms. Kick-start your project with my new book Master Machine Learning Algorithms, including step-by-step tutorials and the […]

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Model Selection Tips From Competitive Machine Learning

Last Updated on June 7, 2016 After spot checking algorithms on your problem and tuning the better few, you ultimately need to select one or two best models with which to proceed. This problem is called model selection and can be vexing because you need to make a choice given incomplete information. This is where the test harness you create and test options you choose are critical. In this post you will discover the tips for model selection inspired from […]

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How to Research a Machine Learning Algorithm

Last Updated on August 12, 2019 Algorithms are a big part of the field of machine learning. You need to understand what algorithms are out there, and how to use them effectively. An easy way to shortcut this knowledge is to review what is already known about an algorithm, to research it. In this post you will discover the importance of researching machine learning algorithms and the 5 different sources that you can use to accelerate your understanding of machine […]

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How To Investigate Machine Learning Algorithm Behavior

Last Updated on December 13, 2019 Machine learning algorithms are complex systems that require study to understand. Static descriptions of machine learning algorithms are a good starting point, but are insufficient to get a feeling for how the algorithm behaves. You need to see the algorithm in action. Experimenting on a running machine learning algorithms will allow you to build an intuition for the cause and effect relationship of the algorithm parameters with the results you can achieve on different […]

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Don’t Start with Open-Source Code When Implementing Machine Learning Algorithms

Last Updated on August 12, 2019 Edward Raff is the author of the Java Machine Learning library called JSAT (which is an acronym for Java Statistical Analysis Tool). Edward has implemented many algorithms in creating this library and I recently reached out to him and asked what advice he could give to beginners implementing machine learning algorithms from scratch. In this post we take a look at tips on implementing machine learning algorithms based on Edwards advice. Kick-start your project with […]

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Take Control By Creating Targeted Lists of Machine Learning Algorithms

Last Updated on August 12, 2019 Any book on machine learning will list and describe dozens of machine learning algorithms. Once you start using tools and libraries you will discover dozens more. This can really wear you down, if you think you need to know about every possible algorithm out there. A simple trick to tackle this feeling and take some control back is to make lists of machine learning algorithms. This ridiculously simple tactic can give you a lot […]

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How To Get Baseline Results And Why They Matter

Last Updated on June 27, 2017 In my courses and guides, I teach the preparation of a baseline result before diving into spot checking algorithms. A student of mine recently asked: If a baseline is not calculated for a problem, will it make the results of other algorithms questionable? He went on to ask: If other algorithms do not give better accuracy than the baseline, what lesson should we take from it? Does it indicate that the data set does not […]

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Hello World of Applied Machine Learning

Last Updated on September 5, 2016 It is easy to feel overwhelmed with the large numbers of machine learning algorithms. There are so many to choose from, it is hard to know where to start and what to try. The choice can be paralyzing. You need to get over this fear and start. There is no magic book or course that is going to tell you what algorithm to use and when. In fact, in practice you cannot know this […]

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Machine Learning Q&A: Concept Drift, Better Results and Learning Faster

Last Updated on June 7, 2016 I get a lot of questions about machine learning via email and I love answering them. I get to see what real people are doing and help to make a difference. (Do you have a question about machine learning? Contact me). In this post I highlight a few of the interesting questions I have received recently and summarize my answers. Machine Learning Q&APhoto by Angelo Amboldi, some rights reserved Why does my spam classifier […]

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