eBooki
W kategorii eBooki znajdziesz książki w postaci elektronicznej, w formie PDF, ePub oraz mobi. Po zakupie e-booka będzie on dostępny w Bibliotece na koncie użytkownika. Książki przeczytasz na laptopie, tablecie, smartfonie lub czytniku ebooków (Kindle, Pocketbook, inkBOOK, Prestigio i innych). Więcej na temat wykorzystania i zabezpieczenia eBooków znajdziesz na stronie "Przewodnik po eBookach".
Ebooki dostępne w księgarni Ebookpoint
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Uczenie maszynowe z użyciem Scikit-Learn i TensorFlow
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Uczenie maszynowe w Pythonie. Receptury
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Uczenie maszynowe dla programistów
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Zaawansowane uczenie maszynowe z językiem Python
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Zwinna analiza danych. Apache Hadoop dla każdego
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Transforming Healthcare with DevOps. A practical DevOps4Care guide to embracing the complexity of digital transformation
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Simplifying Android Development with Coroutines and Flows. Learn how to use Kotlin coroutines and the flow API to handle data streams asynchronously in your Android app
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Introduction to Machine Learning with Python. A Guide for Data Scientists
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Practical Machine Learning with H2O. Powerful, Scalable Techniques for Deep Learning and AI
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Thoughtful Machine Learning with Python. A Test-Driven Approach
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Data Science i uczenie maszynowe
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Deep Learning. A Practitioner's Approach
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Learning TensorFlow. A Guide to Building Deep Learning Systems
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Machine Learning and Security. Protecting Systems with Data and Algorithms
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TensorFlow for Deep Learning. From Linear Regression to Reinforcement Learning
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Deep Learning Cookbook. Practical Recipes to Get Started Quickly
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Natural Language Processing with PyTorch. Build Intelligent Language Applications Using Deep Learning
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The Enterprise Big Data Lake. Delivering the Promise of Big Data and Data Science
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Generative Deep Learning. 2nd Edition
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Designing Data Visualizations. Representing Informational Relationships
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Machine Learning for Email. Spam Filtering and Priority Inbox
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Wzorce projektowe uczenia maszynowego. Rozwiązania typowych problemów dotyczących przygotowania danych, konstruowania modeli i MLOps
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Practical Data Science with SAP. Machine Learning Techniques for Enterprise Data
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Practical Time Series Analysis. Prediction with Statistics and Machine Learning
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Programming PyTorch for Deep Learning. Creating and Deploying Deep Learning Applications
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Practical Automated Machine Learning on Azure. Using Azure Machine Learning to Quickly Build AI Solutions
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Google BigQuery: The Definitive Guide. Data Warehousing, Analytics, and Machine Learning at Scale
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Praktyczne uczenie maszynowe
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TinyML. Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
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Building Machine Learning Powered Applications. Going from Idea to Product
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Building Machine Learning Pipelines
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Machine Learning and Data Science Blueprints for Finance
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AI and Machine Learning for Coders
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Kubeflow for Machine Learning
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Artificial Intelligence in Finance
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Machine Learning Design Patterns
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Python w uczeniu maszynowym
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Praktyczne uczenie nienadzorowane przy użyciu języka Python
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Uczenie maszynowe na Raspberry Pi
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Practical Fairness
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Introducing MLOps
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Kubeflow Operations Guide
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Odsłaniamy SQL Server 2019: Klastry Big Data i uczenie maszynowe
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Przetwarzanie języka naturalnego w akcji
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PyTorch Pocket Reference
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Practical Machine Learning for Computer Vision
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AI and Machine Learning for On-Device Development
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Practical Weak Supervision
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Machine Learning for Hackers. Case Studies and Algorithms to Get You Started
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Natural Language Annotation for Machine Learning
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Practical Machine Learning: A New Look at Anomaly Detection
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Thoughtful Machine Learning. A Test-Driven Approach
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Practical Machine Learning: Innovations in Recommendation
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Machine Learning for Financial Risk Management with Python
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Modern Mainframe Development
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Fundamentals of Deep Learning. 2nd Edition
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Designing Machine Learning Systems
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Natural Language Processing with Transformers, Revised Edition
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Practical Simulations for Machine Learning
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Designing Autonomous AI
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Tidy Modeling with R
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Hands-On Healthcare Data
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Reliable Machine Learning
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Praktyczne uczenie maszynowe w języku R
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Applied Machine Learning and AI for Engineers
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Practicing Trustworthy Machine Learning
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Scaling Machine Learning with Spark
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Machine Learning for High-Risk Applications
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Graph-Powered Analytics and Machine Learning with TigerGraph
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Probabilistic Machine Learning for Finance and Investing
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Architecting Data and Machine Learning Platforms
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Delta Lake: Up and Running
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Training Data for Machine Learning
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Machine Learning Interviews
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Implementing MLOps in the Enterprise
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Deep Learning for Finance
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Hands-On Entity Resolution
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Effective Machine Learning Teams
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Deep Learning at Scale
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Spark. Rozproszone uczenie maszynowe na dużą skalę. Jak korzystać z MLlib, TensorFlow i PyTorch