An Introduction to Feature Selection

Last Updated on August 15, 2020 Which features should you use to create a predictive model? This is a difficult question that may require deep knowledge of the problem domain. It is possible to automatically select those features in your data that are most useful or most relevant for the problem you are working on. This is a process called feature selection. In this post you will discover feature selection, the types of methods that you can use and a […]

September 29, 2020 Machine Learning

Building a Production Machine Learning Infrastructure

Last Updated on June 7, 2016 Midwest.io is was a conference in Kansas City on July 14-15 2014. At the conference, Josh Wills gave a talk on what it takes to build production machine learning infrastructure in a talk titled “From the lab to the factory: Building a Production Machine Learning Infrastructure“. Josh Wills is a the Senior Director of Data Science at Cloudera and formally worked on Google’s ad auction system. In this post you will discover insight into […]

September 29, 2020 Machine Learning

16 Options To Get Started and Make Progress in Machine Learning and Data Science

Last Updated on August 16, 2020 You want to learn machine learning or data science. You might want a job or the opportunity to get a job in machine learning or data science. Alternatively, you might be a student or in a data role and looking to accelerate your learning in the area. If you think your only options are to get a PhD or to read an academic textbook, think again. This post is for you. You have a […]

September 29, 2020 Machine Learning

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 […]

September 29, 2020 Machine Learning

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 […]

September 29, 2020 Machine Learning

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 […]

September 29, 2020 Machine Learning

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 […]

September 29, 2020 Machine Learning

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 […]

September 29, 2020 Machine Learning

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 […]

September 29, 2020 Machine Learning

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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