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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...
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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...
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Machine learning best practices: Autotune models to avoid local minimum...
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...
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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...
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Bots, collusion and accountability in pricing
In the recent article, “Price-bots can collude against consumers,” the Economist discusses the consumer effects of prices set by price-bots. The article starts with an example of gasoline pricing...
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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...
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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...
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Is deep learning the latest fad?
In my 25 years at SAS, I‘ve noticed the continued use of important algorithms, such as logistic regression and decision trees, which I’m sure will continue to be steady staples for data scientists....
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Machine learning concepts: styles of machine learning
This is the first in a series of posts about machine learning concepts, where we'll cover everything from learning styles to new dimensions in machine learning research. What makes machine learning so...
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Online learning: Machine learning’s secret for big data
In the field of machine learning, online learning refers to the collection of machine learning methods that learn from a sequence of data provided over time. In online learning, models update...
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Interpretability is crucial for trusting AI and machine learning
As machine learning takes its place in many recent advances in science and technology, the interpretability of machine learning models grows in importance. We are surrounded with applications powered...
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Understanding and interpreting your data set
Don`t jump into modelling. First, understand and explore your data! This is common advice for many data scientists. If your data set is messy, building models will not help you to solve your problem....
View ArticleHow to build deep learning models with SAS
SAS® supports the creation of deep neural network models. Examples of these models include convolutional neural networks, recurrent neural networks, feedforward neural networks and autoencoder neural...
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From Aristotle to Pi: Practical advice from a chief data scientist
What can you learn from a chief data scientist who's worked in analytics for for 25 years and has been involved in the development of many key SAS solutions, including SAS Enterprise Miner? As a...
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Recurrent neural networks: An essential tool for machine learning
Sequence models, especially recurrent neural network (RNN) and similar variants, have gained tremendous popularity over the last few years because of their unparalleled ability to handle unstructured...
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Interpret model predictions with partial dependence and individual...
Continuing our series on model interpretability, this post explains two methods for plotting variables that can give insight into how a model is working. This is the third post in our interpretability...
View ArticleUsing deep learning to forecast solar energy
Did you know that SAS has two on-site solar farms? At a combined 2.3 MW in capacity, SAS’ solar farms are located on 12 acres at world headquarters in Cary, NC. The photovoltaic (PV) solar arrays...
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Top three video resources for machine learning newbies
Several weeks ago, I wrote about practical advice from a Chief Data Scientist in my blog “From Aristotle to Pi: Practical advice from a chief data scientist.” Now I want to offer my advice as a newbie...
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Automate your feature engineering
In machine learning, a feature is another word for an attribute or input, or an independent variable. What is feature engineering? Feature engineering is a process of preparing inputs for machine...
View ArticleWhy you need GPUs for your deep learning platform
Deep learning has taken off because organizations of all sizes are capturing a greater variety of data and can mine bigger data, including unstructured data. It’s not just large companies like Amazon,...
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