M. - ebooki
Tytuły autora: M. dostępne w księgarni Ebookpoint
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Mastering NLP from Foundations to LLMs. Apply advanced rule-based techniques to LLMs and solve real-world business problems using Python
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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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TinyML Cookbook. Combine machine learning with microcontrollers to solve real-world problems - Second Edition
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Modern Time Series Forecasting with Python. Explore industry-ready time series forecasting using modern machine learning and deep learning
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The Kaggle Book. Data analysis and machine learning for competitive data science
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Transformers for Natural Language Processing. Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4 - Second Edition
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Hands-On Data Analysis with Pandas. A Python data science handbook for data collection, wrangling, analysis, and visualization - Second Edition
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The Deep Learning with Keras Workshop. Learn how to define and train neural network models with just a few lines of code
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The Supervised Learning Workshop. Predict outcomes from data by building your own powerful predictive models with machine learning in Python - Second Edition
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Python Deep Learning. Exploring deep learning techniques and neural network architectures with PyTorch, Keras, and TensorFlow - Second Edition
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Artificial Intelligence By Example. Develop machine intelligence from scratch using real artificial intelligence use cases
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Teradata Cookbook. Over 85 recipes to implement efficient data warehousing solutions
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Building a Recommendation System with R. Learn the art of building robust and powerful recommendation engines using R
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Data Science for Business. What You Need to Know about Data Mining and Data-Analytic Thinking
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Fundamentals of Analytics Engineering. An introduction to building end-to-end analytics solutions
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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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Bayesian Analysis with Python. A practical guide to probabilistic modeling - Third Edition
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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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Microsoft Power BI Performance Best Practices. A comprehensive guide to building consistently fast Power BI solutions
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Praktyczne uczenie maszynowe
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Python w uczeniu maszynowym
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Analiza i prezentacja danych w Microsoft Excel. Vademecum Walkenbacha
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Building Interactive Dashboards in Microsoft 365 Excel. Harness the new features and formulae in M365 Excel to create dynamic, automated dashboards
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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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Building an Event-Driven Data Mesh
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Data Science for Marketing Analytics. A practical guide to forming a killer marketing strategy through data analysis with Python - Second Edition
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Machine Learning Using TensorFlow Cookbook. Create powerful machine learning algorithms with TensorFlow
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The Economics of Data, Analytics, and Digital Transformation. The theorems, laws, and empowerments to guide your organization’s digital transformation
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Microsoft Excel 2013 Budowanie modeli danych przy użyciu PowerPivot
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Machine Learning Design Patterns
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The Deep Learning Workshop. Learn the skills you need to develop your own next-generation deep learning models with TensorFlow and Keras
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The Unsupervised Learning Workshop. Get started with unsupervised learning algorithms and simplify your unorganized data to help make future predictions
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Data Science for Marketing Analytics. Achieve your marketing goals with the data analytics power of Python
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Natural Language Processing with PyTorch. Build Intelligent Language Applications Using Deep Learning
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Solidity Programming Essentials. A beginner's guide to build smart contracts for Ethereum and blockchain
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Big Data Analytics with Java. Data analysis, visualization & machine learning techniques
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Data Science i uczenie maszynowe
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Mastering PostGIS. Modern ways to create, analyze, and implement spatial data
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Kompletny przewodnik po DAX. Analiza biznesowa przy użyciu Microsoft Excel, SQL Server Analysis Services i Power BI
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Wnioskowanie przyczynowe w Pythonie. Praktyczne wykorzystanie w branży technologicznej
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Apache Spark. Kurs video. Przetwarzanie złożonych zbiorów danych
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Excel 2010 PL. Ilustrowany przewodnik
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Mistrz analizy danych. Od danych do wiedzy. Wydanie II
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Unleashing the Power of Data with Trusted AI. A guide for board members and executives
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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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Deep Learning at Scale
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Introduction to Algorithms. A Comprehensive Guide for Beginners: Unlocking Computational Thinking
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Algorithms and Data Structures with Python. A comprehensive guide to data structures & algorithms via an interactive learning experience
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Data Analysis Foundations with Python. Master Data Analysis with Python: From Basics to Advanced Techniques
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Generative Deep Learning with Python. Unleashing the Creative Power of AI by Mastering AI and Python
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Data Modeling with Microsoft Power BI
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Python Data Cleaning Cookbook. Prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn, and OpenAI - Second Edition
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Augmented Analytics
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Privacy-Preserving Machine Learning. A use-case-driven approach to building and protecting ML pipelines from privacy and security threats
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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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Active Machine Learning with Python. Refine and elevate data quality over quantity with active learning
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Artificial Intelligence with Microsoft Power BI
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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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Data Stewardship in Action. A roadmap to data value realization and measurable business outcomes
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Hands-On Entity Resolution
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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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Machine Learning Infrastructure and Best Practices for Software Engineers. Take your machine learning software from a prototype to a fully fledged software system
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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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Automating Data Quality Monitoring
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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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Data Observability for Data Engineering. Proactive strategies for ensuring data accuracy and addressing broken data pipelines
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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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Vector Search for Practitioners with Elastic. A toolkit for building NLP solutions for search, observability, and security using vector search
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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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Data Exploration and Preparation with BigQuery. A practical guide to cleaning, transforming, and analyzing data for business insights
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Synthetic Data for Machine Learning. Revolutionize your approach to machine learning with this comprehensive conceptual guide
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Amazon Redshift: The Definitive Guide
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Practical Data Quality. Learn practical, real-world strategies to transform the quality of data in your organization
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Building ETL Pipelines with Python. Create and deploy enterprise-ready ETL pipelines by employing modern methods
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Learning Data Science
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Data Wrangling on AWS. Clean and organize complex data for analysis
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Azure Data and AI Architect Handbook. Adopt a structured approach to designing data and AI solutions at scale on Microsoft Azure
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AI & Data Literacy. Empowering Citizens of Data Science
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Graph-Powered Analytics and Machine Learning with TigerGraph
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Graph Data Modeling in Python. A practical guide to curating, analyzing, and modeling data with graphs
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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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Geospatial Data Analytics on AWS. Discover how to manage and analyze geospatial data in the cloud
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Zaufanie do systemów sztucznej inteligencji
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Embedded Analytics
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Streaming Data Mesh
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Machine Learning for High-Risk Applications
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CompTIA Data+: DAO-001 Certification Guide. Complete coverage of the new CompTIA Data+ (DAO-001) exam to help you pass on the first attempt
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Computer Vision on AWS. Build and deploy real-world CV solutions with Amazon Rekognition, Lookout for Vision, and SageMaker
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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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The Kaggle Workbook. Self-learning exercises and valuable insights for Kaggle data science competitions
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Tomographic imaging in environmental, industrial and medical applications
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Practicing Trustworthy Machine Learning
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Machine Learning Model Serving Patterns and Best Practices. A definitive guide to deploying, monitoring, and providing accessibility to ML models in production
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Building Analytics Teams. Harnessing analytics and artificial intelligence for business improvement
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Transforming Healthcare with DevOps. A practical DevOps4Care guide to embracing the complexity of digital transformation
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Microsoft Power BI Quick Start Guide. The ultimate beginner's guide to data modeling, visualization, digital storytelling, and more - Third Edition
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Neural Search - From Prototype to Production with Jina. Build deep learning–powered search systems that you can deploy and manage with ease
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Learning Microsoft Power BI
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Data Quality Fundamentals
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Serverless ETL and Analytics with AWS Glue. Your comprehensive reference guide to learning about AWS Glue and its features
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SQL for Data Analytics. Harness the power of SQL to extract insights from data - Third Edition
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Cyfrowe Państwo. Uwarunkowania i perspektywy
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Data Cleaning and Exploration with Machine Learning. Get to grips with machine learning techniques to achieve sparkling-clean data quickly
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Quantum Computing Experimentation with Amazon Braket. Explore Amazon Braket quantum computing to solve combinatorial optimization problems
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Simplifying Data Engineering and Analytics with Delta. Create analytics-ready data that fuels artificial intelligence and business intelligence
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Tidy Modeling with R
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Practical Deep Learning at Scale with MLflow. Bridge the gap between offline experimentation and online production
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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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Modern Time Series Forecasting with Python. Industry-ready machine learning and deep learning time series analysis with PyTorch and pandas - Second Edition
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Python for Algorithmic Trading Cookbook. Recipes for designing, building, and deploying algorithmic trading strategies with Python
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Power Bi. Tworzenie raportów