Apr 
14, 
2020

Continuous Delivery for Machine Learning

In modern software development, we’ve grown to expect that new software features and enhancements will simply appear incrementally, on any given day. This applies to consumer applications such as mobile, web, and desktop apps, as well as modern enterprise software. We’re no longer tolerant of big, disruptive software deployments. ThoughtWorks...

Enjoying the content?

Get the most out of MLcon by becoming a free community member — curated resources, weekly newsletter, and member-only perks.

Weekly
Articles + tutorials

The reads you'd find if you had time

2× / mo
Live webinars

Experts you can actually ask

Monthly
Magazine + whitepapers

Deep dives worth your weekend

On-demand
Recordings + courses

Past conferences, ready when you are

Behind the Tracks

Generative AI & Agents
Unlock the future of AI with LLM advancements.

MLOps & LLMOps
Bridge the gap between model creation and real-world application.

ML & Deep Learning
From Feature Engineering to Explainable AI.

AI Strategy & Governance
Transform business processes with AI-driven strategies.

AI Developer Tools
Build next-generation machine learning applications.

ML Basics & Principles
Gain a solid foundation in core ML concepts.