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