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

Last update: Dec 31, 2022

Related tags

Machine Learning python learning machine-learning cloud machine oreilly-books practical-mlops

Overview

Practical MLOps, an O'Reilly Book

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

Tentative Outline

Chapter 1: Introduction to MLOps

Source Code Chapter 1:

Multi-cloud Github Actions Demo

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

Owner

Pragmatic AI Labs

Experts on cloud native Machine Learning and AI Solutions. One million trained by 2021. #onemillion2021

Pragmatic AI Labs

GitHub Repository

Learn Machine Learning Algorithms by doing projects in Python and R Programming Language

Learn Machine Learning Algorithms by doing projects in Python and R Programming Language. This repo covers all aspect of Machine Learning Algorithms.

6 Oct 20, 2022

This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev

MLProject_01 This project impelemented for midterm of the Machine Learning #Zoomcamp #Alexey Grigorev Context Dataset English question data set file F

1 Dec 18, 2021

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

1 Nov 27, 2021

InfiniteBoost: building infinite ensembles with gradient descent

InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De

183 Jan 03, 2023

Book Recommender System Using Sci-kit learn N-neighbours

Model-Based-Recommender-Engine I created a book Recommender System using Sci-kit learn's N-neighbours algorithm for my model and the streamlit library

1 Jan 13, 2022

Real-time stream processing for python

Streamz Streamz helps you build pipelines to manage continuous streams of data. It is simple to use in simple cases, but also supports complex pipelin

1.1k Dec 28, 2022

BASTA: The BAyesian STellar Algorithm

BASTA: BAyesian STellar Algorithm Current stable version: v1.0 Important note: BASTA is developed for Python 3.8, but Python 3.7 should work as well.

16 Nov 15, 2022

Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

84 Nov 25, 2022

Automatic extraction of relevant features from time series:

tsfresh This repository contains the TSFRESH python package. The abbreviation stands for "Time Series Feature extraction based on scalable hypothesis

7k Jan 06, 2023

Traingenerator 🧙 A web app to generate template code for machine learning ✨

Traingenerator 🧙 A web app to generate template code for machine learning ✨ 🎉 Traingenerator is now live! 🎉

1.2k Jan 07, 2023

List of Data Science Cheatsheets to rule the world

Data Science Cheatsheets List of Data Science Cheatsheets to rule the world. Table of Contents Business Science Business Science Problem Framework Dat

11.7k Dec 30, 2022

Contains an implementation (sklearn API) of the algorithm proposed in "GENDIS: GEnetic DIscovery of Shapelets" and code to reproduce all experiments.

GENDIS GENetic DIscovery of Shapelets In the time series classification domain, shapelets are small subseries that are discriminative for a certain cl

90 Oct 28, 2022

A Time Series Library for Apache Spark

Flint: A Time Series Library for Apache Spark The ability to analyze time series data at scale is critical for the success of finance and IoT applicat

970 Jan 04, 2023

Responsible Machine Learning with Python

Examples of techniques for training interpretable ML models, explaining ML models, and debugging ML models for accuracy, discrimination, and security.

624 Jan 06, 2023

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

What is xLearn? xLearn is a high performance, easy-to-use, and scalable machine learning package that contains linear model (LR), factorization machin

3k Jan 08, 2023

Machine Learning for Time-Series with Python.Published by Packt

Machine-Learning-for-Time-Series-with-Python Become proficient in deriving insights from time-series data and analyzing a model’s performance Links Am

124 Dec 28, 2022

Code for the TCAV ML interpretability project

Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim, Martin Wattenberg, Justin Gilmer, C

552 Dec 27, 2022

Napari sklearn decomposition

napari-sklearn-decomposition A simple plugin to use with napari This napari plug

1 Sep 01, 2022

Coursera Machine Learning - Python code

Coursera Machine Learning This repository contains python implementations of certain exercises from the course by Andrew Ng. For a number of assignmen

859 Dec 10, 2022

As we all know the BGMI Loot Crate comes with so many resources for the gamers, this ML Crate will be the hub of various ML projects which will be the resources for the ML enthusiasts! Open Source Program: SWOC 2021 and JWOC 2022.

Machine Learning Loot Crate 💻 🧰 🔴 Welcome contributors! As we all know the BGMI Loot Crate comes with so many resources for the gamers, this ML Cra

89 Dec 28, 2022