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по запросу «ML» · найдено 30
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Книги

30
Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow

Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow

Hannes Hapke, Catherine Nelson
Машинное обучение. Проектирование систем от идеи до реализации

Машинное обучение. Проектирование систем от идеи до реализации

Валерий Бабушкин, Арсений Кравченко
Machine Learning Platform Engineering: Build an internal developer platform for ML and AI systems

Machine Learning Platform Engineering: Build an internal developer platform for ML and AI systems

Benjamin Tan Wei Hao, Shanoop Padmanabhan, Varun Mallya
MLOps with Ray: Best Practices and Strategies for Adopting Machine Learning Operations

MLOps with Ray: Best Practices and Strategies for Adopting Machine Learning Operations

Hien Luu, Max Pumperla, Zhe Zhang
Serverless Machine Learning with Amazon Redshift ML: Create, train, and deploy machine learning models using familiar SQL commands

Serverless Machine Learning with Amazon Redshift ML: Create, train, and deploy machine learning models using familiar SQL commands

Debu Panda, Phil Bates, Bhanu Pittampally, Sumeet Joshi
Applied Machine Learning and High-Performance Computing on AWS

Applied Machine Learning and High-Performance Computing on AWS

Mani Khanuja, Farooq Sabir, Shreyas Subramanian, Trenton Potgieter
Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications

Chip Huyen
Машинное обучение с малым объемом кодирования

Машинное обучение с малым объемом кодирования

Гвендолин Стриплинг, Майкл Абель
Deploy Machine Learning Models to Production: With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform

Deploy Machine Learning Models to Production: With Flask, Streamlit, Docker, and Kubernetes on Google Cloud Platform

Pramod Singh
The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions

The Pragmatic Programmer for Machine Learning: Engineering Analytics and Data Science Solutions

Marco Scutari, Mauro Malvestio
System Design. Подготовка к сложному интервью по GenAI

System Design. Подготовка к сложному интервью по GenAI

Аминиан Али, Шенг Хао
Applied Machine Learning: Using Machine Learning to Solve Business Problems

Applied Machine Learning: Using Machine Learning to Solve Business Problems

Jason Hodson
Explainable AI for Practitioners: Designing and Implementing Explainable ML Solutions

Explainable AI for Practitioners: Designing and Implementing Explainable ML Solutions

Michael Munn, David Pitman
System Design. Машинное обучение. Подготовка к сложному интервью

System Design. Машинное обучение. Подготовка к сложному интервью

Алекс Сюй, Али Аминиан
Машинное обучение в Elastic Stack

Машинное обучение в Elastic Stack

Рич Кольер, Камилла Монтонен, Бахаалдин Азарми
Чисто функциональные структуры данных

Чисто функциональные структуры данных

Крис Окасаки
Azure Machine Learning

Azure Machine Learning

Jeff Barnes
Машинное обучение в структурной биологии

Машинное обучение в структурной биологии

Головин Андрей Викторович, Пензар Дмитрий Дмитриевич
Python Machine Learning By Example. Fourth Edition

Python Machine Learning By Example. Fourth Edition

Yuxi (Hayden) Liu
Designing Deep Learning Systems: A Guide for Software Engineers

Designing Deep Learning Systems: A Guide for Software Engineers

Chi Wang, Donald Szeto, Yan Xue
Beginner’s Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications

Beginner’s Guide to Streamlit with Python: Build Web-Based Data and Machine Learning Applications

Sujay Raghavendra
Fundamentals of Software Engineering: Comprehensive insights into SDLC, design, quality and AI/ML in software

Fundamentals of Software Engineering: Comprehensive insights into SDLC, design, quality and AI/ML in software

Dr. Hitesh Mohapatra, Dr. Amiya Kumar Rath
Machine Learning in Production: Master the art of delivering robust Machine Learning solutions with MLOps

Machine Learning in Production: Master the art of delivering robust Machine Learning solutions with MLOps

Suhas Pote
Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines

Hands-On Machine Learning with C++: Build, train, and deploy end-to-end machine learning and deep learning pipelines

Kirill Kolodiazhnyi
Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques

Machine Learning for Imbalanced Data: Tackle imbalanced datasets using machine learning and deep learning techniques

Kumar Abhishek, Dr. Mounir Abdelaziz
Learning AutoML: Automating ML Pipelines with AutoGluon, Leading Frameworks, and Real-World Integration

Learning AutoML: Automating ML Pipelines with AutoGluon, Leading Frameworks, and Real-World Integration

Kerem Tomak
Artificial Intelligence for Robotics: Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML techniques for real-world tasks

Artificial Intelligence for Robotics: Build intelligent robots using ROS 2, Python, OpenCV, and AI/ML techniques for real-world tasks

Francis X. Govers III
Проектирование систем машинного обучения

Проектирование систем машинного обучения

Чип Хьюен (Chip Huyen)
Computer Science From Scratch: Building Interpreters, Art, Emulators, and ML in Python

Computer Science From Scratch: Building Interpreters, Art, Emulators, and ML in Python

David Kopec
Машинное обучение. Паттерны проектирования

Машинное обучение. Паттерны проектирования

Валлиаппа Лакшманан, Сара Робинсон, Майкл Мунн