Engineering MLOps
by Emmanuel Raj
Get up and running with machine learning life cycle management and implement MLOps in your organization Key FeaturesBecome well-versed with MLOps techniques to monitor the quality of machine learning models in productionExplore a monitoring framework for ML models in production and learn about end-to-end traceability f…
22 AI-mapped connections to other books on Hikara
Books that ECHO Engineering MLOps
Reads that harmonize with similar ideas, themes, or philosophies.
Practical Lakehouse Architecture
Gaurav Ashok Thalpati
Build a Career in Data Science
Emily Robinson, Jacqueline Nolis
Designing Machine Learning Systems
Chip Huyen
Practical MLOps
Noah Gift, Alfredo Deza
Learn Docker in a Month of Lunches, Second Edition
Elton Stoneman
Building Data Science Applications with FastAPI
François Voron
Scaling Machine Learning with Spark
Adi Polak
Fundamentals of Data Engineering
Joe Reis, Matt Housley
Learning Spark
Jules S. Damji, Brooke Wenig, Tathagata Das, Denny Lee
Machine Learning Algorithms in Depth
Vadim Smolyakov
Books that BRIDGE from Engineering MLOps
Cross-domain reads that transfer ideas into new fields.
Deep Learning from Scratch
Seth Weidman
Modern Data Analytics in Excel
George Mount
R for Data Science
Hadley Wickham, Mine Çetinkaya-Rundel, Garrett Grolemund
Applied Machine Learning
Jason Hodson
Learn Microsoft Power BI
Greg Deckler
Python Crash Course, 3rd Edition
Eric Matthes
Grokking Algorithms, Second Edition
Aditya Y Bhargava
Fundamentals for Self-Taught Programmers
Jasmine Greenaway
Data Science from Scratch
Joel Grus
Hands-On Machine Learning with Scikit-Learn and PyTorch
Aurélien Géron
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