machine learning best practices Posts

Tag: machine learning best practices

10 Machine Learning Tips from Chief Data Scientist Wayne Thompson.

Austin CookJune 3, 2020 0

A monotonic relationship exists when a model’s output increases or stays constant in step with an increase in your model’s inputs. Relationships can be monotonically increasing or decreasing with the distinction based on which direction the input and output travel. A common example is in credit risk where you would expect someone’s risk score to increase with the amount of debt they have relative to their income.

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Banking | Insurance

Advanced Analytics | Machine Learning

Wayne ThompsonSeptember 12, 2017 0

Machine learning best practices: Add features to training data

This is the final post in my series of machine learning best practices. If you missed the earlier posts, start at the beginning, or read the whole series by clicking on the image to the right. While post four in the series was about combining different types of models, this

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Advanced Analytics | Machine Learning

Wayne ThompsonSeptember 5, 2017 0

Machine learning best practices: Understanding generalization

This is the seventh post in my series of machine best practices. Catch up by reading the first post or the whole series now. Generalization is the learned model’s ability to fit well to new, unseen data instead of the data it was trained on. Overfitting refers to a model that fits

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Advanced Analytics | Machine Learning

Wayne ThompsonAugust 25, 2017 0

Machine learning best practices: Manage the temporal effect

This is the sixth post in my series of machine learning best practices. If you've come across the series for the first time, you can go back to the beginning or read the whole series. Aristotle was likely one of the first data scientists who studied empiricism by learning through

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Advanced Analytics | Machine Learning

Wayne ThompsonAugust 10, 2017 0

Machine learning best practices: Autotune models to avoid local minimum breakdowns

This is the fifth post in my series of machine learning best practices. Hyperparameters are the algorithm options one "turns and tunes" when building a learning model. Hyperparameters cannot be learned using that algorithm. So, these parameters need to be assigned before training of the model. A lot of manual

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Advanced Analytics | Machine Learning

Wayne ThompsonAugust 3, 2017 0

Machine learning best practices: Put your models to work

This is the fourth post in my series of 10 machine learning best practices. It’s common to build models on historical training data and then apply the model to new data to make decisions. This process is called model deployment or scoring. I often hear data scientists say, “It took

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Advanced Analytics | Machine Learning

Wayne ThompsonJuly 25, 2017 0

Machine learning best practices: combining lots of models

This is the third post in my series of machine learning techniques and best practices. If you missed the earlier posts, read the first one now, or review the whole machine learning best practices series. Data scientists commonly use machine learning algorithms, such as gradient boosting and decision forests, that automatically build

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Advanced Analytics | Machine Learning

two charts show under sampling and oversampling

Wayne ThompsonJuly 19, 2017 0

Machine learning best practices: detecting rare events

This is the second post in my series of machine learning best practices. If you missed it, read the first post, Machine learning best practices: the basics. As we go along, all ten tips will be archived at this machine learning best practices page. Machine learning commonly requires the use of

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Advanced Analytics | Machine Learning

Wayne ThompsonJuly 12, 2017 0

Machine learning best practices: the basics

I started my training in machine learning at the University of Tennessee in the late 1980s. Of course, we didn’t call it machine learning then, and we didn’t call ourselves data scientists yet either. We used terms like statistics, analytics, data mining and data modeling. Regardless of what you call

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