Deep Learning, NLP, NMT, AI, ML
Last Updated on April 21, 2018 I have seen people that think that they need to get a degree in machine learning. I am all for degrees, I just don’t think they are for everyone. I also know that you can get started in machine learning and go far without a degree. In this post I will convince you that you do not need to get a degree in machine learning to get started or make progress in the field […]
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Last Updated on November 8, 2018 Programming is a part of machine learning, but machine learning is much larger than just programming. In this post you will learn that you do not have to be a programmer to get started in machine learning or find solutions to complex problems. Programming Machine Learning Machine learning algorithms are implemented in code. Programmers like implementing algorithms themselves to really understand how an algorithm works. This can also be required to get the most […]
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Last Updated on June 14, 2019 When making a start in a new field it is common to feel overwhelmed. You may lack confidence or feel as though you are not good enough or that you are lacking some prerequisite. You will explore these issues in this post and learn that such feelings can lead to actions that can consume a lot of time and resources and leave you feeling disappointed in yourself. You will learn that there are many […]
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Last Updated on August 12, 2019 Implementing a machine learning algorithm in code can teach you a lot about the algorithm and how it works. In this post you will learn how to be effective at implementing machine learning algorithms and how to maximize your learning from these projects. Kick-start your project with my new book Master Machine Learning Algorithms, including step-by-step tutorials and the Excel Spreadsheet files for all examples. Let’s get started. Photo by Maura McDonnell, some rights […]
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Last Updated on August 16, 2020 There are a lot of good books on machine learning, but most people buy the wrong ones. A question I get asked the most is what books should people buy to get stared in machine learning. My answer to beginners is: “don’t buy textbooks“. In this post I want to point out a few key books that are aimed at beginners that you should buy (and read!) if you are just starting out. I […]
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Last Updated on June 18, 2016 There is no right way to get into machine learning. We all learn slightly different ways and have different objectives of what we want to do with or for machine learning. A common goal is to get productive with machine learning quickly. If that is your goal then this post highlights five common mistakes programmers make on the path to quickly being productive machine learning practitioners. Mistakes Programmers Make when Starting in Machine LearningPhoto […]
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Last Updated on September 29, 2016 There are a lot of machine learning books and courses available and a trend towards free university courses and ebooks. With so much excellent resources available it can feel overwhelming. So much so that it may prevent you from getting started or making progress. In this post I want to share with you my tips for self study that allow me to touch a resource once, extract everything I think I can learn from […]
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Last Updated on August 16, 2020 Machine learning is an iterative process rather than a linear process that requires each step to be revisited as more is learned about the problem under investigation. This iterative process can require using many different tools, programs and scripts for each process. A machine learning workbench is a platform or environment that supports and facilitates a range of machine learning activities reducing or removing the need for multiple tools. Some statistical and machine learning […]
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Last Updated on August 16, 2020 Spot-checking algorithms is about getting a quick assessment of a bunch of different algorithms on your machine learning problem so that you know what algorithms to focus on and what to discard. Photo by withassociates, some rights reserved In this post you will discover the 3 benefits of spot-checking algorithms, 5 tips for spot-checking on your next problem and the top 10 most popular data mining algorithms that you could use in your suite […]
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Last Updated on July 5, 2019 The Systematic Process For Working Through Predictive Modeling ProblemsThat Delivers Above Average Results Over time, working on applied machine learning problems you develop a pattern or process for quickly getting to good robust results. Once developed, you can use this process again and again on project after project. The more robust and developed your process, the faster you can get to reliable results. In this post, I want to share with you the skeleton […]
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