Yada Pruksachatkun, Matthew Mcateer, Subho Majumdar - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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Spark. Rozproszone uczenie maszynowe na dużą skalę. Jak korzystać z MLlib, TensorFlow i PyTorch
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Prompt Engineering - zostań Panem Sztucznej Inteligencji
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Unleashing the Power of Data with Trusted AI. A guide for board members and executives
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Tableau Certified Data Analyst Certification Guide. Ace the Tableau Data Analyst certification exam with expert guidance and practice material
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Getting Started with DuckDB. A practical guide for accelerating your data science, data analytics, and data engineering workflows
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Data Engineering with Databricks Cookbook. Build effective data and AI solutions using Apache Spark, Databricks, and Delta Lake
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Data Governance Handbook. A practical approach to building trust in data
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The Ultimate Guide to Snowpark. Design and deploy Snowpark with Python for efficient data workloads
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Wnioskowanie i związki przyczynowe w Pythonie. Nowoczesne uczenie maszynowe z wykorzystaniem bibliotek DoWhy, EconML, PyTorch i nie tylko
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Data Quality in the Age of AI. Building a foundation for AI strategy and data culture
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Azure Data Engineer Associate Certification Guide. Ace the DP-203 exam with advanced data engineering skills - Second Edition
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Predictive Analytics for the Modern Enterprise
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Databricks ML in Action. Learn how Databricks supports the entire ML lifecycle end to end from data ingestion to the model deployment
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Data Analytics for Marketing. A practical guide to analyzing marketing data using Python
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Accelerate Model Training with PyTorch 2.X. Build more accurate models by boosting the model training process
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Data Engineering with Google Cloud Platform. A guide to leveling up as a data engineer by building a scalable data platform with Google Cloud - Second Edition
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Extending Excel with Python and R. Unlock the potential of analytics languages for advanced data manipulation and visualization
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The Machine Learning Solutions Architect Handbook. Practical strategies and best practices on the ML lifecycle, system design, MLOps, and generative AI - Second Edition
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Aplikacje ChatGPT. Wejdź na wyższy poziom z inteligentnymi programami - generatory, boty i wiele innych!
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Engineering Data Mesh in Azure Cloud. Implement data mesh using Microsoft Azure's Cloud Adoption Framework
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Fundamentals of Analytics Engineering. An introduction to building end-to-end analytics solutions
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The Definitive Guide to Data Integration. Unlock the power of data integration to efficiently manage, transform, and analyze data
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The Definitive Guide to Power Query (M). Mastering complex data transformation with Power Query
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Artificial Intelligence with Microsoft Power BI
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Machine Learning: Make Your Own Recommender System. Build Your Recommender System with Machine Learning Insights
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Machine Learning with Python. Unlocking AI Potential with Python and Machine Learning
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AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide. The ultimate guide to passing the MLS-C01 exam on your first attempt - Second Edition
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Cracking the Data Science Interview. Unlock insider tips from industry experts to master the data science field
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Data-Centric Machine Learning with Python. The ultimate guide to engineering and deploying high-quality models based on good data
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Effective Machine Learning Teams
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Learn Microsoft Fabric. A practical guide to performing data analytics in the era of artificial intelligence
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Transformers for Natural Language Processing and Computer Vision. Explore Generative AI and Large Language Models with Hugging Face, ChatGPT, GPT-4V, and DALL-E 3 - Third Edition
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Azure Data Factory Cookbook. Build ETL, Hybrid ETL, and ELT pipelines using ADF, Synapse Analytics, Fabric and Databricks - Second Edition
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Data Stewardship in Action. A roadmap to data value realization and measurable business outcomes
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Bayesian Analysis with Python. A practical guide to probabilistic modeling - Third Edition
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Data Engineering with Scala and Spark. Build streaming and batch pipelines that process massive amounts of data using Scala
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Data Labeling in Machine Learning with Python. Explore modern ways to prepare labeled data for training and fine-tuning ML and generative AI models
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MLOps with Red Hat OpenShift. A cloud-native approach to machine learning operations
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Principles of Data Science. A beginner's guide to essential math and coding skills for data fluency and machine learning - Third Edition
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Specyfikacja wymagań oprogramowania. Kluczowe praktyki analizy biznesowej
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Jak analizować dane z biblioteką Pandas. Praktyczne wprowadzenie. Wydanie II
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Data Science for Web3. A comprehensive guide to decoding blockchain data with data analysis basics and machine learning cases
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Deep Learning with MXNet Cookbook. Discover an extensive collection of recipes for creating and implementing AI models on MXNet
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The Definitive Guide to Google Vertex AI. Accelerate your machine learning journey with Google Cloud Vertex AI and MLOps best practices
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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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Web Data Mining z użyciem języka Python. Odkrywaj i wyodrębniaj informacje ze stron internetowych za pomocą języka Python
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Data Modeling with Microsoft Excel. Model and analyze data using Power Pivot, DAX, and Cube functions
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Machine Learning for Imbalanced Data. Tackle imbalanced datasets using machine learning and deep learning techniques
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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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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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Power BI i sztuczna inteligencja. Jak w pełni wykorzystać funkcje AI dostępne w Power BI
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Zostań Milionerem z ChatGPT. Prosty przewodnik jak osiągnąć sukces w każdej branży za pomocą sztucznej inteligencji
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Cracking the Data Engineering Interview. Land your dream job with the help of resume-building tips, over 100 mock questions, and a unique portfolio
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Data Science: The Hard Parts
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Alteryx Designer Cookbook. Over 60 recipes to transform your data into insights and take your productivity to a new level
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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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Synthetic Data for Machine Learning. Revolutionize your approach to machine learning with this comprehensive conceptual guide
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Analityk danych. Przewodnik po data science, statystyce i uczeniu maszynowym
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Delta Lake: Up and Running
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Google Analytics od podstaw. Analiza wpływu biznesowego i wyznaczanie trendów
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Microsoft Power BI dla zaawansowanych. Eksperckie techniki tworzenia interaktywnych analiz w świecie biznesu. Wydanie II
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Amazon Redshift: The Definitive Guide
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Building ETL Pipelines with Python. Create and deploy enterprise-ready ETL pipelines by employing modern methods
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Machine Learning with LightGBM and Python. A practitioner's guide to developing production-ready machine learning systems
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Streamlit for Data Science. Create interactive data apps in Python - Second Edition
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Machine Learning for Emotion Analysis in Python. Build AI-powered tools for analyzing emotion using natural language processing and machine learning
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Quantum Computing Algorithms. Discover how a little math goes a long way
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Debugging Machine Learning Models with Python. Develop high-performance, low-bias, and explainable machine learning and deep learning models
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Learning Data Science
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Machine Learning Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition
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Microsoft Power BI. Jak modelować i wizualizować dane oraz budować narracje cyfrowe. Wydanie III
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AI w Biznesie: Praktyczny Przewodnik Stosowania Sztucznej Inteligencji w Różnych Branżach
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Przetwarzanie języka naturalnego w praktyce. Przewodnik po budowie rzeczywistych systemów NLP
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Fundamentals of Data Observability
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Probabilistic Machine Learning for Finance and Investing
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Data Wrangling with SQL. A hands-on guide to manipulating, wrangling, and engineering data using SQL
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Graph-Powered Analytics and Machine Learning with TigerGraph
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Cost-Effective Data Pipelines
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Driving Data Quality with Data Contracts. A comprehensive guide to building reliable, trusted, and effective data platforms
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Enhancing Deep Learning with Bayesian Inference. Create more powerful, robust deep learning systems with Bayesian deep learning in Python
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Exploratory Data Analysis with Python Cookbook. Over 50 recipes to analyze, visualize, and extract insights from structured and unstructured data
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Geospatial Data Analytics on AWS. Discover how to manage and analyze geospatial data in the cloud
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Natural Language Understanding with Python. Combine natural language technology, deep learning, and large language models to create human-like language comprehension in computer systems
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Potoki danych. Leksykon kieszonkowy. Przenoszenie i przetwarzanie danych na potrzeby ich analizy
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Embedded Analytics
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Streaming Data Mesh
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Data Augmentation with Python. Enhance deep learning accuracy with data augmentation methods for image, text, audio, and tabular data
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Machine Learning for High-Risk Applications
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Pierwsze kroki w Power BI. Kompletny przewodnik po praktycznej analityce biznesowej. Wydanie II
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Siatka danych. Nowoczesna koncepcja samoobsługowej infrastruktury danych
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Building an Event-Driven Data Mesh
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Wizualizacja danych. Pulpity nawigacyjne i raporty w Excelu
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Poznaj Microsoft Power BI. Przekształcanie danych we wnioski
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Machine Learning in Microservices. Productionizing microservices architecture for machine learning solutions
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Zaawansowana analiza danych w PySpark. Metody przetwarzania informacji na szeroką skalę z wykorzystaniem Pythona i systemu Spark
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Scaling Machine Learning with Spark
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Applied Geospatial Data Science with Python. Leverage geospatial data analysis and modeling to find unique solutions to environmental problems
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The Kaggle Workbook. Self-learning exercises and valuable insights for Kaggle data science competitions
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Spark. Błyskawiczna analiza danych. Wydanie II
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Data Analytics Using Splunk 9.x. A practical guide to implementing Splunk’s features for performing data analysis at scale
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Modelowanie danych z Power BI dla ekspertów analityki. Jak w pełni wykorzystać możliwości Power BI
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Practicing Trustworthy Machine Learning
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Applied Deep Learning on Graphs. Leveraging Graph Data to Generate Impact Using Specialized Deep Learning Architectures
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Managing Data as a Product. A comprehensive guide to designing and building data product-centered socio-technical architectures
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Pandas Cookbook. Practical recipes for scientific computing, time series and exploratory data analysis using Python - Third Edition
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Becoming a Data Analyst. A beginner's guide to kickstarting your data analysis journey
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Causal Inference in R. Decipher complex relationships with advanced R techniques for data-driven decision making
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Learn Quantum Computing with Python and IBM Quantum. Write your own practical quantum programs with Python - Second Edition
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Python Feature Engineering Cookbook. A complete guide to crafting powerful features for your machine learning models - Third Edition
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Generative AI Engineering, 1E. Build apps with transformer and diffusion-based large and foundational models
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Data Analysis with Polars. Get up and running with Polars to perform effective data analysis with Rust
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15 Math Concepts Every Data Scientist Should Know. Understand and learn how to apply the math behind data science algorithms
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Essential Guide to LLMOps. Implementing effective LLMOps strategies and tools from data to deployment
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Microsoft Power BI Cookbook. Convert raw data into business insights with updated techniques, use cases, and best practices - Third Edition
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Python Machine Learning By Example. Unlock machine learning best practices with real-world use cases - Fourth Edition
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Model Risk Management in Practice. A hands-on guide helping you with the design, implementation, monitoring, and reporting of Model Risk
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Google Machine Learning and Generative AI for Solutions Architects. Build efficient and scalable AI/ML solutions on Google Cloud
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Hands-On Image Processing with Python. Advanced Methods for Analyzing, Transforming, and Interpreting Digital Images with Expertise - Second Edition