The Launchpad

Applied Machine Learning best practices

2,566 35 Followers
Editors
Malika Cantor

@Google | Applied AI & ML | Startups

Cassie Kozyrkov

Chief Decision Intelligence Engineer, Google. ❤️ Stats, ML/AI, data, puns, art, theatre, decision science. All views are my own. twitter.com/quaesita

Adam Kell

Product guy, recovering VC. Curious and passionate builder, lifelong learner.

Maya Sagi Grossman

VP of Marketing @Colu. I write about marketing, startups & tech. I have OCD so please don't touch my shit!

Latest Posts

Your Deep-Learning-Tools-for-Enterprises Startup Will Fail

I usually write about how to integrate and launch ML/AI in consumer-facing products. However, a large part of my job is building ML/AI…

The ML Surprise

When I was in college, an ice cream shop opened nearby, and a few friends and I went to check it out. We walked in, and it looked…

Spinning up an annotation team

Modern tech companies’ core defensibility is often in rapidly building proprietary datasets. These are generally niche datasets that can…

How to protect your Machine Learning product from time, adversaries, and itself

Unlike traditional products, the launch of ML/AI-driven features or products is just the start of a Product Manager’s role. ML models…

Modular Machine Learning in Healthcare

It’s hard to imagine developing software that isn’t modular. It would be extremely difficult to debug, troubleshoot, and implement…

Planning for Machine Learning as a Medtech Startup

As the world transitions to machine learning-powered products and solutions, many subject matter experts will need to develop new skills…

Decentralizing Machine Learning

New tools enable some of the benefits of machine learning (ML) without the risks inherent in centralization. We believe that

Data: A key requirement for your Machine Learning (ML) product

As Product Managers, we have to play the product-equivalent of three-dimensional chess by trying to solve for user, engineering, marketing…

Retracing your steps in Machine Learning: Versioning

Anyone who has tried to build a machine learning model has seen first-hand how fragile a new prediction system can be in dealing with any…

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