Solving the Real Issues with the MLflow Team - ML 059

Solving the Real Issues with the MLflow Team - ML 059

If you’re looking for a team that actually cares about the issues you’re facing, look no further than Databricks, and they’ve got something exciting out. In this episode, Michael and Ben welcome on the development team of MLflow, an open-source lifecycle manager for machine learning. They cover how Databricks is redefining how developers and engineers collaborate, the reason behind Databricks’ crazy success, and the number ONE most important testing structure for any development team. “A lot of the success was attributed to process and dedicated focus on the interface, understanding what major problems we were going after. ”
- Corey Zumar In This Episode How Databricks allows data analysis, engineers, and developers to collaborate effectively
Why Databricks was able to rake in 800,000 downloads per MONTH in their first year
A simple but powerful methodology that helps Databrick identify the highest ROI problems to tackle (not just the most popular ones)
The number one MOST important testing structure that reveals how Databricks keeps their work top-notch
What makes Databricks unique from everyone else and is the KEY to putting users first in 2022 Sponsors Special Guests: Corey Zumar, Harutaka Kawamura, Weichen Xu, and Zhang Jin.Sponsored By:

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Avsnitt(209)

Why Authenticity Beats Algorithms: The New Rules of Digital Marketing - ML 185

Why Authenticity Beats Algorithms: The New Rules of Digital Marketing - ML 185

In this episode, we dive deep into the evolving landscape of digital marketing and brand storytelling. We explore how the intersection of authenticity, community, and technology is reshaping how brand...

4 Apr 202555min

Integrating Business Needs and Technical Skills in Effective Model Serving Deployments - ML 184

Integrating Business Needs and Technical Skills in Effective Model Serving Deployments - ML 184

Welcome back to another episode of Adventures in Machine Learning, where hosts Michael Berk and Ben Wilson delve into the intricate process of implementing model serving solutions. In this episode, th...

13 Feb 202551min

Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183

Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183

Welcome to another insightful episode of Top End Devs, where we delve into the fascinating world of machine learning and data science. In this episode, host Charles Max Wood is joined by special guest...

24 Jan 202555min

Cows, Camels, and the Human Brain - ML 182

Cows, Camels, and the Human Brain - ML 182

What do cows and camels have to do with the human brain? The latest developments in machine learning, of course! In this episode, Michael and Ben dive into a new white paper from Facebook AI researche...

9 Jan 202542min

A/B Testing with ML ft. Michael Berk - ML 181

A/B Testing with ML ft. Michael Berk - ML 181

Michael Berk joins the adventure to discuss how he uses Machine Learning within the context of A/B testing features within applications and how to know when you have a viable test option for your setu...

2 Jan 202545min

Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180

Navigating Build vs. Buy Decisions in Emerging AI Technologies - ML 180

In today's episode, we dive into the critical decision-making process of building versus buying technology solutions, especially when it comes to agentic logic-based frameworks. With the industry stil...

26 Dec 202431min

Artificial Intelligence as a Service with Peter Elger and Eóin Shanaghy - ML 179

Artificial Intelligence as a Service with Peter Elger and Eóin Shanaghy - ML 179

Peter Elger and Eóin Shanaghy join Charles Max Wood to dive into what Artificial Intelligence and Machine Learning related services are available for people to use. Peter and Eóin are experts in AWS a...

19 Dec 202454min

Combating Burnout in Machine Learning: Strategies for Balance and Collaboration - ML 178

Combating Burnout in Machine Learning: Strategies for Balance and Collaboration - ML 178

In this episode, Ben and Michael explore burnout, particularly in machine learning and data science. They highlight that burnout stems from exhaustion, cynicism, and inefficiency and can be caused by ...

12 Dec 20241h 12min

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