This is a public repo where code samples are stored for the book Practical MLOps.

Overview

Practical MLOps, an O'Reilly Book

This is a public repo where code samples are stored for the book Practical MLOps.

mlops-color

Tentative Outline

Chapter 1: Introduction to MLOps

Source Code Chapter 1:

Chapter 2: MLOps Foundations

Source Code Chapter 2:

Chapter 3: Machine Learning Deployment In Production Strategies

Source Code Chapter 3:

Chapter 4: Continuous Delivery for Machine Learning Models

Source Code Chapter 4:

Chapter 5: AutoML

Source Code Chapter 5:

Chapter 6: Monitoring and Logging for Machine Learning

Source Code Chapter 6:

Chapter 7: MLOps for AWS

Source Code Chapter 7:

Chapter 8: MLOps for Azure

Source Code Chapter 8:

Chapter 9: MLOps for GCP

Source Code Chapter 9:

Chapter 10: Machine Learning Interoperability

Source Code Chapter 10:

Chapter 11: Building MLOps command-line tools

Source Code Chapter 11:

Chapter 12: Machine Learning Engineering and MLOps Case Studies

Source Code Chapter 12:

Community Recipes

This section includes "community" recipes. Many "may" be included in the book if timing works out.

References

Next Steps: Take Coursera MLOps Course

cloud-specialization

Owner
Pragmatic AI Labs
Experts on cloud native Machine Learning and AI Solutions. One million trained by 2021. #onemillion2021
Pragmatic AI Labs
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CrayLabs and user contibuted examples of using SmartSim for various simulation and machine learning applications.

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A naive Bayes model for cancer classification using a set of documents

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Code for the TCAV ML interpretability project

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Getting Profit and Loss Make Easy From Binance I have been in Binance Automated Trading for some time and have generated a lot of transaction records,

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Sleep stages are classified with the help of ML. We have used 4 different ML algorithms (SVM, KNN, RF, NN) to demonstrate them

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Anirudh Edpuganti 3 Apr 03, 2022
Pydantic based mock data generation

This library offers powerful mock data generation capabilities for pydantic based models. It can also be used with other libraries that use pydantic as a foundation, for example SQLModel, Beanie and

Na'aman Hirschfeld 396 Dec 28, 2022
Sequence learning toolkit for Python

seqlearn seqlearn is a sequence classification toolkit for Python. It is designed to extend scikit-learn and offer as similar as possible an API. Comp

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Forecasting prices using Facebook/Meta's Prophet model

CryptoForecasting using Machine and Deep learning (Part 1) CryptoForecasting using Machine Learning The main aspect of predicting the stock-related da

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A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search (Manhattan Distance Heuristic)

A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and the A* Search (using the Manhattan Distance Heuristic)

17 Aug 14, 2022
This is the code repository for LRM Stochastic watershed model.

LRM-Squannacook Input data for generating stochastic streamflows are observed and simulated timeseries of streamflow. their format needs to be CSV wit

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Open MLOps - A Production-focused Open-Source Machine Learning Framework Open MLOps is a set of open-source tools carefully chosen to ease user experi

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