Machine Learning — księgarnia Helion — strona 13

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The Potential of Generative AI

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Machine Learning Security with Azure. Best practices for assessing, securing, and monitoring Azure Machine Learning workloads

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Developing Kaggle Notebooks. Pave your way to becoming a Kaggle Notebooks Grandmaster

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Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications

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Databricks Lakehouse Platform Cookbook

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Linux Magazine (grudzień 2022)

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Data Science for Malware Analysis. A comprehensive guide to using AI in detection, analysis, and compliance

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Mastering MLOps Architecture: From Code to Deployment

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Praktyczna algebra liniowa dla analityków danych. Od podstawowych koncepcji do użytecznych aplikacji w Pythonie

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Praktyczna algebra liniowa dla analityków danych. Od podstawowych koncepcji do użytecznych aplikacji w Pythonie

Mike Cohen

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Building Recommendation Systems in Python and JAX

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Developing IoT Projects with ESP32. Unlock the full Potential of ESP32 in IoT development to create production-grade smart devices - Second Edition

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Implementing MLOps in the Enterprise

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

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Sztuczna inteligencja w Azure. Kurs video. Uczenie maszynowe i Azure Machine Learning Service

Marcin Szeliga

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Vector Search for Practitioners with Elastic. A toolkit for building NLP solutions for search, observability, and security using vector search

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Machine Learning Interviews

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TinyML Cookbook. Combine machine learning with microcontrollers to solve real-world problems - Second Edition

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Practical Machine Learning on Databricks. Seamlessly transition ML models and MLOps on Databricks

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Web scraping w Data Science. Kurs video. Uczenie maszynowe i architektura splotowych sieci neuronowych

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Training Data for Machine Learning

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Python Data Science. Niezbędne narzędzia do pracy z danymi. Wydanie II

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Data Science: The Hard Parts

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Interpretable Machine Learning with Python. Build explainable, fair, and robust high-performance models with hands-on, real-world examples - Second Edition

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