Machine Learning

Embrace Randomness in Machine Learning

Last Updated on August 12, 2019 Why Do You Get Different Results On Different Runs Of An Algorithm With The Same Data? Applied machine learning is a tapestry of breakthroughs and mindset shifts. Understanding the role of randomness in machine learning algorithms is one of those breakthroughs. Once you get it, you will see things differently. In a whole new light. Things like choosing between one algorithm and another, hyperparameter tuning and reporting results. You will also start to see the abuses […]

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Machine Learning

Deploy Your Predictive Model To Production

Last Updated on September 30, 2016 5 Best Practices For Operationalizing Machine Learning. Not all predictive models are at Google-scale. Sometimes you develop a small predictive model that you want to put in your software. I recently received this reader question: Actually, there is a part that is missing in my knowledge about machine learning. All tutorials give you the steps up until you build your machine learning model. How could you use this model? In this post, we look at […]

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Machine Learning

How Beginners Get It Wrong In Machine Learning

Last Updated on October 3, 2016 The 5 Most Common Mistakes That Beginners MakeAnd How To Avoid Them. I help beginners get started in machine learning. But I see the same mistakes in both mindset and action again and again. In this post, you will discover the 5 most common ways that I see beginners slip-up when getting started in machine learning. I firmly believe thatanyone can get started and do really wellwith applied machine learning. Hopefully, you can identify yourself […]

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Machine Learning

Stop Coding Machine Learning Algorithms From Scratch

Last Updated on August 12, 2019 You Don’t Have To Implement Algorithms…if you’re a beginner and just getting started. Stop. Are you implementing a machine learning algorithm at the moment? Why? Implementing algorithms from scratch is one of the biggest mistakes I see beginners make. In this post you will discover: The algorithm implementation trap that beginners fall into. The very real difficulty of engineering world-class implementations of machine learning algorithms. Why you should be using off-the-shelf implementations. Kick-start your […]

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Machine Learning

Machine Learning In A Year

Per Went From Developer To Machine Learning Practitioner,And So Can You! Per Borgen is an inspiration. He transitioned from developer to machine learning practitioner. And he explained how he did it. In this post, you will discover the lessons learned by Per on his transition. You will discover two methodologies he adopted and how you can use them. And you will discover the advice Per has for beginners, like you, that are also looking to make the transition. And you […]

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Machine Learning

The Machine Learning Mastery Method

5-Steps To Get Started and Get Good at Machine Learning I teach a 5-step process that you can use to get your start in applied machine learning. It is unconventional. The traditional way to teach machine learning is bottom-up. Start with the theory and math, then algorithm implementations, then send you off to figure out how to start solving real-world problems. The traditional approach to getting started in machine learning has a gap on the path to practitioner. The Machine […]

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Machine Learning

How to Load Machine Learning Data From Scratch In Python

Last Updated on December 11, 2019 You must know how to load data before you can use it to train a machine learning model. When starting out, it is a good idea to stick with small in-memory datasets using standard file formats like comma separated value (.csv). In this tutorial you will discover how to load your data in Python from scratch, including: How to load a CSV file. How to convert strings from a file to floating point numbers. […]

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Machine Learning

How to Scale Machine Learning Data From Scratch With Python

Last Updated on December 11, 2019 Many machine learning algorithms expect data to be scaled consistently. There are two popular methods that you should consider when scaling your data for machine learning. In this tutorial, you will discover how you can rescale your data for machine learning. After reading this tutorial you will know: How to normalize your data from scratch. How to standardize your data from scratch. When to normalize as opposed to standardize data. Kick-start your project with my […]

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Machine Learning

How to Implement Resampling Methods From Scratch In Python

Last Updated on August 13, 2019 The goal of predictive modeling is to create models that make good predictions on new data. We don’t have access to this new data at the time of training, so we must use statistical methods to estimate the performance of a model on new data. This class of methods are called resampling methods, as they resampling your available training data. In this tutorial, you will discover how to implement resampling methods from scratch in […]

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Machine Learning

How To Implement Machine Learning Metrics From Scratch in Python

Last Updated on August 13, 2019 After you make predictions, you need to know if they are any good. There are standard measures that we can use to summarize how good a set of predictions actually are. Knowing how good a set of predictions is, allows you to make estimates about how good a given machine learning model of your problem, In this tutorial, you will discover how to implement four standard prediction evaluation metrics from scratch in Python. After […]

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