"Different ML Algorithms, Different MLOps Challenges"

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Book	Author(s)	Year	Publisher
Supports ML-29-B, ML-29-D, ML-29-E; Anemometers ML-80, ML-80-A, ML-80-B; Indicators ML-117, ML-117-A, ML-117-B	United States. War Department	1944-09-12	U.S. G.P.O.
Clinometers ML-119-C, ML-119-D, ML-119-E, And ML-119-F	United States. War Department	1945	U.S. G.P.O.
Barometers, ML-2 Through ML-2-F, Cases, ML-48 Through ML-48-E	United States War Department	1944	U.S. G.P.O.
MLOps Engineering at Scale	Carl Osipov	2022	Manning
Hands-On Machine Learning with ML. NET: Getting started with Microsoft ML. NET to implement popular machine learning algorithms in C#	Jarred Capellman	2020	Packt Publishing
Different Power Quality Detection Algorithms Using Windowing Technique		15/01/2014	Association of Scientists, Developers and Faculties
Different Power Quality Detection Algorithms Using Windowing Technique	"Priaz Madappillil, Jose Mathew, Able Eldhose, Anoop Thomas	29/12/2013	Association of Scientists, Developers and Faculties
Trh-i ml	'Abdrramn Vef	1912	an'at KÃ¼tÃ¼bhnesi
Elementary Standard ML	Greg Michaelson	December 1995	Springer
Generators ML-185-A And ML-185-B (Hydrogen)	United States. War Department	1945	U.S. G.P.O.
Psychrometer Equipments ML-313/AM and ML-313A/AM	United States Department of the Army	1950-06-12	U.S. G.P.O.
Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps	Valliappa Lakshmanan, Sara Robinson, Michael Munn	2020	O'Reilly Media
Machine Learning Design Patterns: Solutions to Common Challenges in Data Preparation, Model Building, and MLOps	Valliappa Lakshmanan	2020	O'Reilly Media, Inc, USA
Practical MLOps: Operationalizing Machine Learning Models	Noah Gift, Alfredo Deza	2021	O'Reilly Media
Concurrent Programming in ML	John H. Reppy	1999-08	Cambridge University Press
Programming in standard ML	Harper R.	2005
Programming in Standard ML	Robert Harper
Elements of ML programming /	Ullman, Jeffrey D.,	1998.	Prentice Hall,
Elements of ML programming	Jeffrey D. Ullman	1994	Prentice Hall
St Sol Ml/Trigonometry	Lial; Miller; Hornsby	November 13, 1992	Longman
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Different ML Algorithms, Different MLOps Challenges		Introducing MLOps: How to Scale Machine Learning in the Enterprise	Mark Treveil, Nicolas Omont, Clément Stenac, Kenji Lefevre, Du Phan, Joachim Zentici, Adrien Lavoillotte, Makoto Miyazaki, Lynn Heidmann	2020	O'Reilly Media
63 Different ML algorithms		Blockchain and Machine Learning for e-Healthcare Systems	Balusamy Balamurugan (editor), Naveen Chilamkurti (editor), T. Lucia Agnes Beena (editor), T. Poongodi (editor)	2021	Institution of Engineering and Technology
Understanding MLOps challenges		Practical Deep Learning at Scale with MLflow: Bridge the gap between offline experimentation and online production	Yong Liu	2022	Packt Publishing
Adopting MLOps for ML workflows		The Machine Learning Solutions Architect Handbook: Create machine learning platforms to run solutions in an enterprise setting	David Ping	2022	Packt Publishing
Productionizing custom ML models with MLOps		Architecting Google Cloud Solutions: Learn to design robust and future-proof solutions with Google Cloud technologies	Victor Dantas	2021	Packt Publishing
Critical Challenges in MLOps		Practical MLOps: Operationalizing Machine Learning Models	Noah Gift, Alfredo Deza	2021	O'Reilly Media
ML challenges		The Machine Learning Solutions Architect Handbook: Create machine learning platforms to run solutions in an enterprise setting	David Ping	2022	Packt Publishing
OpenCV ML Algorithms		Learning OpenCV	Gary Bradski, Adrian Kaehler	2008	O'Reilly
Classifying ML algorithms		Mastering Azure Machine Learning: Execute Large-Scale End-to-end Machine Learning with Azure	Christoph Korner; Marcel Alsdorf	2022	Packt Publishing, Limited
BigQuery ML algorithms		Machine Learning with BigQuery ML: Create, execute, and improve machine learning models in BigQuery using standard SQL queries	Alessandro Marrandino	2021	Packt Publishing
OpenCV ML Algorithms		Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library	Adrian Kaehler; Gary Bradski	2016	O'Reilly Media
18 ML Algorithms		Data Science Desktop Survival Guide	G J Williams	2021
MLOps challenges for the edge		Intelligent Workloads at the Edge: Deliver cyber-physical outcomes with data and machine learning using AWS IoT Greengrass	Indraneel Mitra, Ryan Burke	2022	Packt Publishing
Defining MLOps and Its Challenges		Introducing MLOps: How to Scale Machine Learning in the Enterprise	Mark Treveil, Nicolas Omont, Clément Stenac, Kenji Lefevre, Du Phan, Joachim Zentici, Adrien Lavoillotte, Makoto Miyazaki, Lynn Heidmann	2020	O'Reilly Media
MLOps (H2O MLOps)		Machine Learning at Scale with H2O: A practical guide to building and deploying machine learning models on enterprise systems	Gregory Keys, David Whiting	2022	Packt Publishing
MLOps		Practical MLOps: Operationalizing Machine Learning Models	Noah Gift, Alfredo Deza	2021	O'Reilly Media
MLOps		Getting Started with Amazon SageMaker Studio: Learn to build end-to-end machine learning projects in the SageMaker machine learning IDE	Michael Hsieh	2022
MLOps		Machine Learning at Scale with H2O: A practical guide to building and deploying machine learning models on enterprise systems	Gregory Keys, David Whiting	2022	Packt Publishing
MLOps		AI-Powered Business Intelligence: Improving Forecasts and Decision Making with Machine Learning	Tobias Zwingmann	2022	O'Reilly Media
MLOps and CI/CD for ML on GCP		Architecting Google Cloud Solutions: Learn to design robust and future-proof solutions with Google Cloud technologies	Victor Dantas	2021	Packt Publishing
Chapter	Author(s)	Book	Book Authors	Year	Publisher

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