Category: Machine Learning

Articles About Machine Learning

Machine Learning

How to Think About Machine Learning

Last Updated on August 15, 2019 Machine learning is a large and interdisciplinary field of study. You can achieve impressive results with machine learning and find solutions to very challenging problems. But this is only a small corner of the broader field of machine learning often called predictive modeling or predictive analytics. In this post, you will discover how to change the way you think about machine learning in order to best serve you as a machine learning practitioner. After […]

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Machine Learning

So, You are Working on a Machine Learning Problem…

Last Updated on January 9, 2019 So, you’re working on a machine learning problem. I want to really nail down where you’re at right now. Let me make some guesses… So, You are Working on a Machine Learning Problem…Photo by David Mulder, some rights reserved. 1) You Have a Problem So you have a problem that you need to solve. Maybe it’s your problem, an idea you have, a question, or something you want to address. Or maybe it is […]

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Machine Learning

How to Make Predictions with scikit-learn

Last Updated on January 10, 2020 How to predict classification or regression outcomeswith scikit-learn models in Python. Once you choose and fit a final machine learning model in scikit-learn, you can use it to make predictions on new data instances. There is some confusion amongst beginners about how exactly to do this. I often see questions such as: How do I make predictions with my model in scikit-learn? In this tutorial, you will discover exactly how you can make classification […]

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Machine Learning

How to Make Predictions with Keras

Last Updated on August 27, 2020 Once you choose and fit a final deep learning model in Keras, you can use it to make predictions on new data instances. There is some confusion amongst beginners about how exactly to do this. I often see questions such as: How do I make predictions with my model in Keras? In this tutorial, you will discover exactly how you can make classification and regression predictions with a finalized deep learning model with the […]

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Machine Learning

Machine Learning Development Environment

The development environment that you use for machine learning may be just as important as the machine learning methods that you use to solve your predictive modeling problem. A few times a week, I get a question such as: What is your development environment for machine learning? In this post, you will discover the development environment that I use and recommend for applied machine learning for developers. After reading this post, you will know: The important distinctions between the role […]

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Machine Learning

Analytical vs Numerical Solutions in Machine Learning

Do you have questions like: What data is best for my problem? What algorithm is best for my data? How do I best configure my algorithm? Why can’t a machine learning expert just give you a straight answer to your question? In this post, I want to help you see why no one can ever tell you what algorithm to use or how to configure it for your specific dataset. I want to help you see that finding good data/algorithm/configuration […]

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Machine Learning

How to Get the Most From Your Machine Learning Data

Last Updated on June 30, 2020 The data that you use, and how you use it, will likely define the success of your predictive modeling problem. Data and the framing of your problem may be the point of biggest leverage on your project. Choosing the wrong data or the wrong framing for your problem may lead to a model with poor performance or, at worst, a model that cannot converge. It is not possible to analytically calculate what data to […]

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Machine Learning

The Model Performance Mismatch Problem (and what to do about it)

What To Do If Model Test Results Are Worse than Training. The procedure when evaluating machine learning models is to fit and evaluate them on training data, then verify that the model has good skill on a held-back test dataset. Often, you will get a very promising performance when evaluating the model on the training dataset and poor performance when evaluating the model on the test set. In this post, you will discover techniques and issues to consider when you […]

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Machine Learning

How To Know if Your Machine Learning Model Has Good Performance

After you develop a machine learning model for your predictive modeling problem, how do you know if the performance of the model is any good? This is a common question I am asked by beginners. As a beginner, you often seek an answer to this question, e.g. you want someone to tell you whether an accuracy of x% or an error score of x is good or not. In this post, you will discover how to answer this question for […]

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Machine Learning

Introduction to Random Number Generators for Machine Learning in Python

Last Updated on July 31, 2020 Randomness is a big part of machine learning. Randomness is used as a tool or a feature in preparing data and in learning algorithms that map input data to output data in order to make predictions. In order to understand the need for statistical methods in machine learning, you must understand the source of randomness in machine learning. The source of randomness in machine learning is a mathematical trick called a pseudorandom number generator. […]

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