Software 2.0 and Snorkel: Beyond Hand-Labeled Data
This ODSC West 2018 talk “Software 2.0 and Snorkel: Beyond Hand-Labeled Data,” presented by Alex Ratner, a Ph.D. student in Computer Science at Stanford University, discusses a new way of effectively programming machine learning systems using what’s called “weaker supervision,” and how it enables domain experts... Read more
Wonders in Image Processing with Machine Learning
We discuss some wonders in the field of image processing with machine learning advancements. Image processing can be defined as the technical analysis of an image by using complex algorithms. Here, image is used as the input, where the useful information returns as the output. According... Read more
The Best Machine Learning Research of September 2019
Every month brings its own wave of exciting research, and September was as busy a month as ever for developments in machine learning. To help sort through everything, we’ve compiled our five favorite machine learning research papers of the month, check them out below.  [Related Article:... Read more
RAPIDS Forest Inference Library: Prediction at 100 Million Rows per Second
Random forests (RF) and gradient-boosted decision trees (GBDTs) have become workhorse models of applied machine learning. XGBoost and LightGBM, popular packages implementing GBDT models, consistently rank among the most commonly used tools by data scientists on the Kaggle platform. We see similar interest in forest-based models... Read more
Automating Image Annotation with MAX
This blogpost introduces automating image annotation with MAX (Model Asset Exchange). To learn more about how our deep learning models are created, containerized, and deployed to production, come join our training at ODSC West 2019: Deploying Deep Learning Models as Microservices.  Introduction The Model Asset Exchange (MAX)... Read more
Unpacking YouTube’s Recommender System
Over the past couple of years, YouTube has come under fire for its recommender system, with the media suggesting that it is promoting violent content, or banning LGBT content for violating its terms of service. Seemingly in response to all of this, Google has finally released... Read more
Composable Machine Learning
Even as machine learning (ML) algorithms become more sophisticated and powerful, the way ML teams build ML systems hasn’t changed much. In this article, we’ll explain the need for composable machine learning systems. First, take a look at the old, inefficient way. Once the team figures... Read more
Applications of AI in Cybersecurity
Editor’s Note: See Dustin’s talk “Applications of AI in Cybersecurity” at ODSC West 2019. Security has historically lagged behind the implementation of new technology. With AI/ML transforming how industries and government agencies do business and serve citizens, it is critical that developers build security into our... Read more
Using GANs to Generate Images of Race Cars
Have you ever stood in a packed crowd, seen heatwaves rippling off the pavement and felt the roar of cars flying past you? No? I’m guessing that the overlap of ODSC blog readers and car racing fans might be small. However, those roaring cars do present... Read more
Visualizing Vectors: Basics Every Data Scientist Should Know
This ODSC West 2018 talk “Visualizing Vectors: Basics Every Data Scientist Should Know,” presented by Jed Crosby, Head of Data Science at Clari, should be a required learning resource for all new data scientists. This is because every data scientist should have a firm grasp of... Read more