Turning a Keras Model into an Estimator
Google’s TensorFlow engine has a unique way of solving problems, allowing us to solve machine learning problems very efficiently. Nowadays, machine learning is used in almost all areas of life and work, with famous applications in computer vision, speech recognition, language translations, healthcare, and many more. ... Read more
Overcoming the Cold Start Problem: How to Make New Tasks Tractable
I woke up this morning (somewhat unsurprisingly). After poking my head out of the covers and feeling a cold chill in the air, I made the executive decision not to proceed with this course of action and promptly withdrew back under the covers. Ten minutes later,... Read more
Announcing the ODSC Machine Learning Certification
A successful data scientist or AI practitioner never stops learning. However, pausing your career to return to school for another degree can be costly in terms of both time and budget. In such situations, machine learning certifications are an essential tool for both developing new skills... Read more
Civic Data Science for the Charles River Watershed Association
When you hear the phrase “corporate data science,” what comes to mind? You may think of recommender systems for video streaming platforms or optimizing the click-through rate for online advertisements. When thinking about “academic data science,” maybe you are reminded of some white papers on arXiv.org... Read more
Fast, Visual, and Explainable ML Modeling With PerceptiLabs
Pure-code ML frameworks like TensorFlow, have become popular for building ML models because they effectively offer a high-level grammar for describing model topologies and algorithms. This is a powerful approach, but it has limitations for providing insight and explainability of models. These issues are further magnified... Read more
Simplifying MLOps with Model Registry
Your iPhone tells you exactly what app you’d like to access each morning, Netflix shows you movie previews that are tailored precisely for you, and Grammarly fixes your writing so you sound like your best self! Each of these applications is the product of a team... Read more
Your Guide to Linear Regression Models
Interpretability is one of the biggest challenges in machine learning. A model has more interpretability than another one if its decisions are easier for a human to comprehend. Some models are so complex and are internally structured in such a way that it’s almost impossible to... Read more
Why Causal Machine Learning is the Next Revolution in AI
Editor’s note: Robert Ness is a speaker for ODSC East 2021. Check out his talk, “Causal Machine Learning Blitz,” there! Causal modeling and inference are perhaps at the core of the most interesting questions in data science. A common task for a data scientist at a... Read more
Linear Regression in Machine Learning
In every phase of our daily lives, we use different machine learning technologies to find appropriate solutions. These algorithms not only identify text, audio, video or images, but are quite instrumental in improving some other aspects that include the marketing sector, customer services, medical sectors, and a... Read more
Best Machine Learning Research of 2020
2020 will be remembered as a year chock full of significant challenges, but for data science, specifically AI, machine learning, and deep learning, the march forward continued unabated. We saw excellent progress with enterprise acceptance of machine learning across a wide swath of industries and problem... Read more