data science
Your AI Survival Guide
Keep it Clean: Why Bad Data Ruins Projects and How to Fix it
Cloud-Native Data Science: Turning Data-Oriented Business Problems Into Scalable Solutions
One does not simply put Machine Learning into Production
Inextricably Linked: Reproducibility and Productivity in Data Science and AI
Deliver Results, Not Just Releases: Control & Observability in CD
Robot DJs: Better Spotify Playlists through Music Theory and Discrete Optimization
ChatGPT from Scratch: How to Train an Enterprise AI Assistant
Why Most Data Projects Fail and How to Avoid It
How to Leverage Reinforcement Learning
Quantum Computing in Practice
What is Data Science and Where is it Heading?
The Importance of Reinforcement Learning with Phil Winder
Is Machine Learning a Black Box?
What Does It Take To Be a Data Scientist?
How AutoML & Low Code Empowers Data Scientists
Chanuki Illushka Seresinhe
Zoopla
Head of Data Science at Zoopla & Co-founder of Beautiful Places AI
Phil Winder
Winder Research
CEO of Winder.AI, author of "Reinforcement Learning"
Nicholai Stålung
Trifork
Data scientist who has spawned and led multiple data science and ML teams
Katharine Jarmul
Probably Private
Privacy/Security Expert at Probably Private & O'Reilly Author
Jim Webber
Neo4j
Working on a variety of database research topics with a focus on fault-tolerance at Neo4j
Joe Reis
Ternary Data
Co-Author of "Fundamentals of Data Engineering", Speaker, Professor & Podcaster
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