Practical AI: Machine Learning, Data Science, LLM

Killer developer tools for machine learning

Nov 9, 2020

50:40

Creator website

AI Chapters

Episode notes

Introduction

3min

How to Be a Practical AI Strategist

2min

How I Got Interrupted in AI and Computer Science

3min

Gradient Descent: A Podcast for Practitioners

2min

How to Start a Machine Learning Company

5min

The Next Layer in the Stack: Developer Tools

3min

The Balance Between Passion and Passion

2min

The Importance of Open Air in the Startup Workflow

3min

The Pain Points of ML Tooling

3min

10.

Contextual Comparisons in Model Trains

3min

11.

How to Capture System Metrics

2min

12.

The Differences Between DevOps and Data Ops

3min

13.

How to Address Variability in Modeling

2min

14.

How to Integrate Weights and Biases Into ML Workflows

3min

15.

The Evolution of Weights and Biases in Data Versioning

4min

16.

Git: A New Concept for Software Development

3min

17.

How to Use a Web Browser to Do Authentication

2min

18.

The Future of Tooling

2min

19.

The Importance of Listening

3min

Weights & Biases is coming up with some awesome developer tools for AI practitioners! In this episode, Lukas Biewald describes how these tools were a direct result of pain points that he uncovered while working as an AI intern at OpenAI. He also shares his vision for the future of machine learning tooling and where he would like to see people level up tool-wise.

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