Deep learning is gaining an immense amount of popularity due to the incredible results that it is able to offer with comparatively little effort. Because of this there are a number of engineers who are trying their hand at building machine learning models with the wealth of frameworks that are available. Andrew Ferlitsch wrote a book to capture the useful patterns and best practices for building models with deep learning to make it more approachable for newcomers ot the field. In this episode he shares his deep expertise and extensive experience in building and teaching machine learning across many companies and industries. This is an entertaining and educational conversation about how to build maintainable models across a variety of applications.
AnnouncementsThe intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA
Update Your Model's View Of The World In Real Time With Streaming Machine Learning Using River
Declarative Machine Learning For High Performance Deep Learning Models With Predibase
Build Better Machine Learning Models With Confidence By Adding Validation With Deepchecks
Build A Full Stack ML Powered App In An Afternoon With Baseten
Skip Straight To The Fun Part Of Your Project With PyScaffold
Add Configuration Best Practices To Your Application In An Afternoon With Dynaconf
Take A Tour Of The Hidden Language Of Hardware And How It Powers Your Code
Take Control Of Your Electrical Systems With The Open Source FlexMeasures Energy Management System
How And Why To Build Effective Teams As An Engineering Leader
Complete Your Hardware "Weekend Projects" In An Actual Weekend With Belay
Catching Up With Pyre, A Fast Type Checker For Python
Standardizing On Python For All Software Projects At Ascend.io
Exploring The Process And Practice Of Building Better Software Through Code Reviews
Ship With Confidence By Automating Quality Assurance
Remove Roadblocks And Let Your Developers Ship Faster With Self-Serve Infrastructure
The Benefits Of Python And Django For Going From Zero To MVP At Speed
Powering The Next Generation Of Application Architectures With Web Assembly And The Fermyon Platform
Gain A Deeper Understanding Of What Your Code Is Doing And Where It Spends Its Time With VizTracer
Stream Processing In Real Time And At Scale In Pure Python With Bytewax
Tetra: A Full Stack Web Framework That Doesn't Make You Write Everything Twice
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