Keys to Building Machine Learning Systems • Garrett Smith • GOTO 2020
This presentation was recorded at GOTO Chicago 2020. #GOTOcon #GOTOchgo
http://gotochgo.com
Garrett Smith – Founder at Guild AI and Chicago ML
ABSTRACT
In this session, you learn engineering techniques for building machine learning systems. Machine learning methods are capable of delivering immense business value. But machine learning is still not leveraged in many organizations. Engineering challenges and lack of software and systems experience are leading causes. The solution is to apply engineering practices to machine learning systems development end-to-end.
Garrett Smith presents keys to successful ML systems development. These include methods for working with data scientists, common tool sets, and automation. You learn the importance of short, iterative release cycles for data science. You learn how to show business value early in a project. With this information, you’re better […]
TIMECODES
00:00 Intro
01:21 What is machine learning?
02:04 AI adoption in the enterprise 2020
05:30 The fundamental problem in most organizations
06:07 Data science vs. traditional software
08:58 ML systems development
14:14 Unify data science & engineering teams
15:43 Use software best practices
16:57 Identify model success criteria metrics
19:20 Solve a simple problem first
20:10 Automate end-to-end on day 1
22:22 Ongoing refactoring with tests
25:05 Keys to building ML systems (summary)
Download slides and read the full abstract here:
https://gotochgo.com/2020/sessions/1414/keys-to-building-machine-learning-systems
RECOMMENDED BOOKS
Holden Karau, Trevor Grant, Boris Lublinsky, Richard Liu & Ilan Filonenko • Kubeflow for Machine Learning • https://amzn.to/3JVngcx
Phil Winder • Reinforcement Learning • https://amzn.to/3t1S1VZ
Kelleher & Tierney • Data Science (The MIT Press Essential Knowledge series) • https://amzn.to/3AQmIRg
Lakshmanan, Robinson & Munn • Machine Learning Design Patterns • https://amzn.to/2ZD7t0x
Lakshmanan, Görner & Gillard • Practical Machine Learning for Computer Vision • https://amzn.to/3m9HNjP
Aurélien Géron • Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow • https://amzn.to/2XZaQy8
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