Choosing Machine Learning Algorithms: Lessons from Microsoft Azure

Last Updated on August 12, 2019 Microsoft recently launched support for machine learning in their Azure cloud computing platform. Buried in some of their technical documentation for the platform are some resources that you may find useful for thinking about what machine learning algorithm to use in different situations. In this post we take a look at the Microsoft recommendations for machine learning algorithms and the lessons that we can use when working through machine learning problems on any platform. […]

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Understand Machine Learning Algorithms By Implementing Them From Scratch

Last Updated on August 15, 2020 Implementing machine learning algorithms from scratch seems like a great way for a programmer to understand machine learning. And maybe it is. But there some downsides to this approach too. In this post you will discover some great resources that you can use to implement machine learning algorithms from scratch. You will also discover some of the limitations of this seemingly perfect approach. Kick-start your project with my new book Machine Learning Algorithms From Scratch, […]

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Find Your Machine Learning Tribe

Last Updated on August 15, 2020 Get Started And Avoid Getting The Wrong Advice Machine learning is a fascinating and powerful field of study filled with algorithms and data. The thing is, there are so many different types of people interested in machine learning, and each has different needs. It is important to understand what it is you want from machine learning and to tailor your self-study to those needs. If you don’t, you could very easily go down the rabbit […]

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Data Science From Scratch: Book Review

Last Updated on August 16, 2020 Programmers learn by implementing techniques from scratch. It is a type of learning that is perhaps slower than other types of learning, but fuller in that all of the micro decisions involved become intimate. The implementation is owned from head to tail. In this post we take a close look at Joel Grus popular book “Data Science from Scratch: First Principles with Python“. I recently finished reading the paperback version and I think it […]

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How to Use a Machine Learning Checklist to Get Accurate Predictions, Reliably

Last Updated on August 15, 2020 How do you get accurate results using machine learning on problem after problem? The difficulty is that each problem is unique, requiring different data sources, features, algorithms, algorithm configurations and on and on. The solution is to use a checklist that guarantees a good result every time. In this post you will discover a checklist that you can use to reliably get good results on your machine learning problems. Machine Learning ChecklistPhoto by Crispy, […]

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Gentle Introduction to Predictive Modeling

Last Updated on July 22, 2020 When you’re an absolute beginner it can be very confusing. Frustratingly so. Even ideas that seem so simple in retrospect are alien when you first encounter them. There’s a whole new language to learn. I recently received this question: So using the iris exercise as an example if I were to pluck a flower from my garden how would I use the algorithm to predict what it is? It’s a great question. In this post I […]

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How Do I Get Started In Machine Learning? (the short version)

Last Updated on June 7, 2016 I get daily emails asking the question: How do I get started in machine learning? This post provides my quick answer. Here is my long answer. So here is how to get started in machine learning, the quick version. Practice Creating Predictive Models You’re interested in machine learning but you’re not sure of the specific outcome you’re looking for. Maybe you’re interested in learning more about machine learning algorithms. Maybe you’re interested in creating predictions. […]

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Philosophy Graduate to Machine Learning Practitioner (an interview with Brian Thomas)

Last Updated on August 15, 2020 Getting started in machine learning can be frustrating. There’s so much to learn that it feels overwhelming. So much so that many developers interested in machine learning never get started. The idea of creating models on ad hoc datasets and entering a Kaggle competition sounds exciting a far off goal. So how did a Philosophy graduate get started in machine learning? In this post I interview Brian Thomas. Brian got started in machine learning using a top-down approach of actually practicing applied […]

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Interview: How a Beginner Used Small Projects To Get Started in Machine Learning

Last Updated on August 15, 2020 It is valuable to get insight into how real people are getting started in machine learning. In this post you will discover how a beginner (just like you) got started and is making great progress in applying machine learning. I find interviews like this absolutely fascinating because of all of the things you can learn. I’m sure you will too. Use Small Projects To Get StartedPhoto by pixonomy, some rights reserved. Q. What resources did […]

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Tour of Real-World Machine Learning Problems

Last Updated on September 5, 2016 Real-world examples make the abstract description of machine learning become concrete. In this post you will go on a tour of real world machine learning problems. You will see how machine learning can actually be used in fields like education, science, technology and medicine. Each machine learning problem listed also includes a link to the publicly available dataset. This means that if a particular concrete machine learning problem interest you, you can download the dataset and start […]

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