Full text tutorial with code (requires MLExpert Pro): www.mlexpert.io/bootcamp/arch...
Building a real-world machine learning project can be daunting. How do you create a good pipeline and what tools should you use?
In this video, we'll build a real-world project to predict body fat percentage, utilizing tools like Poetry, DVC, and FastAPI. Learn to manage dependencies, version your data, tune hyperparameters with experiments, and serve predictions with a REST API, all while creating a reproducible pipeline.
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GitHub repository: github.com/curiousily/Get-Thi...
00:00 - Project Overview
00:42 - Introduction
01:29 - Tutorial on MLExpert.io
02:00 - Project start
02:19 - Poetry & VSCode setup
06:50 - Config files
11:13 - Git setup
11:58 - DVC setup
13:26 - Build dataset
22:00 - Build features
29:51 - Train model
33:54 - Hyperparameter tuning with DVC experiments
36:30 - REST API with FastAPI
38:08 - Try the API
39:08 - Conclusion
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Негізгі бет Build Real-World Machine Learning Project: Step-by-Step Guide using FastAPI, DVC & Poetry
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