In this episode I continue the conversation from the previous one, about failing machine learning models.
When data scientists have access to the distributions of training and testing datasets it becomes relatively easy to assess if a model will perform equally on both datasets. What happens with private datasets, where no access to the data can be granted?
At fitchain we might have an answer to this fundamental problem.
AI: The Bubble That Might Pop—What’s Next? (Ep. 262)
Data Guardians: How Enterprises Can Master Privacy with MetaRouter (Ep. 261)
Low-Code Magic: Can It Transform Analytics? (Ep. 260)
Do you really know how GPUs work? (Ep. 259)
Harnessing AI for Cybersecurity: Expert Tips from QFunction (Ep. 258)
Rust in the Cosmos Part 4: What happens in space? (Ep. 257)
Rust in the Cosmos Part 3: Embedded programming for space (Ep. 256)
Rust in the Cosmos Part 2: testing software in space (Ep. 255)
Rust in the Cosmos Part 1: Decoding Communication (Ep. 254)
AI and Video Game Development: Navigating the Future Frontier (Ep. 253)
Kaggle Kommando's Data Disco: Laughing our Way Through AI Trends (Ep. 252)
Revolutionizing Robotics: Embracing Low-Code Solutions (Ep. 251)
Is SQream the fastest big data platform? (Ep. 250)
OpenAI CEO Shake-up: Decoding December 2023 (Ep. 249)
Careers, Skills, and the Evolution of AI (Ep. 248)
Open Source Revolution: AI’s Redemption in Data Science (Ep. 247)
Money, Cryptocurrencies, and AI: Exploring the Future of Finance with Chris Skinner [RB] (Ep. 246)
Debunking AGI Hype and Embracing Reality [RB] (Ep. 245)
Destroy your toaster before it kills you. Drama at OpenAI and other stories (Ep. 244)
The AI Chip Chat 🤖💻 (Ep. 243)
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The Unbelivable Truth - Series 1 - 26 including specials and pilot