Improving your dataset quality is absolutely critical for effective ML. Finding errors in your datasets is generally a slow, iterative, and painstaking process. Data scientists should be proactively fixing their model’s blindspots by improving their training data. In this talk, Yash discusses how Galileo helps data scientists identify, fix, and track data across the entire ML workflow.
In this episode
Co-founder and VP of Engineering, Galileo
Co-founder and VP of Engineering. Prior to starting Galileo, Yash spent the last decade working on Automatic Speech Recognition (ASR) at Google, leading their core speech recognition platform team, that powers speech-to-text across 20+ products at Google in over 80 languages along with thousands of businesses through their Cloud Speech API.
Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.
Dr. Adam Sroka, Head of Machine Learning Engineering at Origami Energy, is an experienced data and AI leader helping organizations unlock value from data by delivering enterprise-scale solutions and building high-performing data and analytics teams from the ground up. Adam shares his thoughts and ideas through public speaking, tech community events, on his blog, and in his podcast.