What is MLops and Why Do You Need it?
Editor’s note: Yinxi is a speaker for ODSC East 2022. Be sure to check out her talk alongside Sean Owen, “MLOps: Relieving Technical Debt in ML with MLflow, Delta and Databricks,” to learn more about MLOps! The past decade has seen huge adoption of Machine Learning... Read more
The New Centerpiece of the ML Tech Stack: The Feature Store
When data scientists train models, they build features specifically for the development environment. But those features have to be rewritten by data engineers to make them production-ready. After many years in the machine learning field and seeing this siloed process occur over and over, I’ve spent... Read more
Top Machine Learning Research for the Second Half of 2021
As 2021 draws to a close, I’m energized by all the amazing work completed by many prominent research groups extending the state of machine learning in a variety of important directions. In this article, I’ll keep you up to date with my top picks of machine... Read more
The Rising Importance of Feature Stores
More and more, we’re seeing data science and data engineering teams turning toward Feature Stores to help manage the data sets and data pipelines needed to productionize machine learning applications. Features, or more formally “feature variables,” arguably are the most important ingredient for successful machine learning.... Read more
Why Your Machine Learning Project Could Fail
When I started my career in data science, I believed that the most difficult part of a project was doing the actual work. I was wrong. Most advanced analytics and machine learning projects fail or don’t reach the production state. The reasons for failure range from... Read more
An Introduction to Decision Tree and Ensemble Methods
In this day and age, there is a lot of buzz around machine learning (ML) and artificial intelligence (AI). And why not, after all, we all are consumers of ML directly or indirectly, irrespective of our professions. AI/ML is a fascinating field, generates a whole lot... Read more
Scale Model Deployment Anywhere with Azure Arc Enabled Machine Learning
The Azure Machine Learning team is excited to announce the public preview of Azure Arc-enabled Machine Learning for inference. This builds on our training preview, enabling customers to deploy and serve models in any infrastructure on-premises and across multi-cloud using Kubernetes. With a simple AzureML extension... Read more
The ODSC Warmup Guide to fastText
fastText is a lightweight Python library that was created to build scalable solutions for text representation and classification. It works on standard and generic hardware, smartphones, and small computers by utilizing functionalities that can reduce the memory consumed for fastText models. In recent years, fastText has... Read more
Since the beginning of the COVID pandemic, there have been more than 700000 scientific papers published on the subject. A human researcher cannot possibly get acquainted with such a huge text corpus — and therefore some help from AI is highly needed. In this post, we... Read more
Graph Representation Learning: From Simple to Higher-order Structures
Editor’s note: Mayank is a speaker for ODSC West 2021. Be sure to check out his talk, “Graph Representation Learning: From Simple to Higher-Order Structures,” there! Graphs and networks have become ubiquitous for describing “complex systems,” where it is not enough to just represent the elements... Read more