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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Automated Machine Learning with AutoKeras. Deep learning made accessible for everyone with just few lines of coding
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Machine Learning with BigQuery ML. Create, execute, and improve machine learning models in BigQuery using standard SQL queries
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Graph Machine Learning. Take graph data to the next level by applying machine learning techniques and algorithms
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Machine Learning with the Elastic Stack. Gain valuable insights from your data with Elastic Stack's machine learning features - Second Edition
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Machine Learning Engineering with Python. Manage the production life cycle of machine learning models using MLOps with practical examples
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Deep Learning with fastai Cookbook. Leverage the easy-to-use fastai framework to unlock the power of deep learning
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Machine Learning with Amazon SageMaker Cookbook. 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments
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Getting Started with Streamlit for Data Science. Create and deploy Streamlit web applications from scratch in Python
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Exploring GPT-3. An unofficial first look at the general-purpose language processing API from OpenAI
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Machine Learning Engineering with MLflow. Manage the end-to-end machine learning life cycle with MLflow
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IBM Cloud Pak for Data. An enterprise platform to operationalize data, analytics, and AI
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Machine Learning for Time-Series with Python. Forecast, predict, and detect anomalies with state-of-the-art machine learning methods
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Python Feature Engineering Cookbook. Over 70 recipes for creating, engineering, and transforming features to build machine learning models
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Hands-On Music Generation with Magenta. Explore the role of deep learning in music generation and assisted music composition
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Mastering Machine Learning Algorithms. Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work - Second Edition
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Deep Learning with R Cookbook. Over 45 unique recipes to delve into neural network techniques using R 3.5.x
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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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Hands-On Machine Learning with ML.NET. Getting started with Microsoft ML.NET to implement popular machine learning algorithms in C#
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Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter. Build scalable real-world projects to implement end-to-end neural networks on Android and iOS
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Hands-On One-shot Learning with Python. Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch
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Hands-On Deep Learning with R. A practical guide to designing, building, and improving neural network models using R
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Mastering Azure Machine Learning. Perform large-scale end-to-end advanced machine learning in the cloud with Microsoft Azure Machine Learning
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Hands-On Machine Learning with C++. Build, train, and deploy end-to-end machine learning and deep learning pipelines
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Hands-On Python Deep Learning for the Web. Integrating neural network architectures to build smart web apps with Flask, Django, and TensorFlow
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Hands-On Mathematics for Deep Learning. Build a solid mathematical foundation for training efficient deep neural networks
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Hands-On Simulation Modeling with Python. Develop simulation models to get accurate results and enhance decision-making processes
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The Deep Learning with PyTorch Workshop. Build deep neural networks and artificial intelligence applications with PyTorch
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The Machine Learning Workshop. Get ready to develop your own high-performance machine learning algorithms with scikit-learn - Second Edition
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Hands-On Machine Learning with scikit-learn and Scientific Python Toolkits. A practical guide to implementing supervised and unsupervised machine learning algorithms in Python
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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 Unsupervised Learning Workshop. Get started with unsupervised learning algorithms and simplify your unorganized data to help make future predictions
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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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Machine Learning for Algorithmic Trading. Predictive models to extract signals from market and alternative data for systematic trading strategies with Python - Second Edition
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The Natural Language Processing Workshop. Confidently design and build your own NLP projects with this easy-to-understand practical guide
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Applied Deep Learning and Computer Vision for Self-Driving Cars. Build autonomous vehicles using deep neural networks and behavior-cloning techniques
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Deep Learning for Beginners. A beginner's guide to getting up and running with deep learning from scratch using Python
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Python Machine Learning By Example. Build intelligent systems using Python, TensorFlow 2, PyTorch, and scikit-learn - Third Edition
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Microsoft Power BI Quick Start Guide. Bring your data to life through data modeling, visualization, digital storytelling, and more - Second Edition
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Codeless Deep Learning with KNIME. Build, train, and deploy various deep neural network architectures using KNIME Analytics Platform
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Hands-On Q-Learning with Python. Practical Q-learning with OpenAI Gym, Keras, and TensorFlow
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Applied Deep Learning with Keras. Solve complex real-life problems with the simplicity of Keras
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PyTorch Deep Learning Hands-On. Build CNNs, RNNs, GANs, reinforcement learning, and more, quickly and easily
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Hands-On Machine Learning with Microsoft Excel 2019. Build complete data analysis flows, from data collection to visualization
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Hands-On Deep Learning Architectures with Python. Create deep neural networks to solve computational problems using TensorFlow and Keras
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Machine Learning for Data Mining. Improve your data mining capabilities with advanced predictive modeling
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Machine Learning with Scala Quick Start Guide. Leverage popular machine learning algorithms and techniques and implement them in Scala
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Deep Learning with R for Beginners. Design neural network models in R 3.5 using TensorFlow, Keras, and MXNet
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Mastering Machine Learning on AWS. Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow
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Advanced Machine Learning with R. Tackle data analytics and machine learning challenges and build complex applications with R 3.5
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Supervised Machine Learning with Python. Develop rich Python coding practices while exploring supervised machine learning
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Machine Learning for Finance. Principles and practice for financial insiders
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Deep Learning for Natural Language Processing. Solve your natural language processing problems with smart deep neural networks
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Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications
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Hands-On Ensemble Learning with Python. Build highly optimized ensemble machine learning models using scikit-learn and Keras
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Hands-On Deep Learning Algorithms with Python. Master deep learning algorithms with extensive math by implementing them using TensorFlow
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Hands-On Deep Learning with Go. A practical guide to building and implementing neural network models using Go
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Practical Machine Learning with R. Define, build, and evaluate machine learning models for real-world applications
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Machine Learning for OpenCV 4. Intelligent algorithms for building image processing apps using OpenCV 4, Python, and scikit-learn - Second Edition
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Java Deep Learning Cookbook. Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j
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Machine Learning for Cybersecurity Cookbook. Over 80 recipes on how to implement machine learning algorithms for building security systems using Python
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Hands-On Machine Learning with TensorFlow.js. A guide to building ML applications integrated with web technology using the TensorFlow.js library
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Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2 - Third Edition
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Advanced Deep Learning with Python. Design and implement advanced next-generation AI solutions using TensorFlow and PyTorch
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Advanced Deep Learning with R. Become an expert at designing, building, and improving advanced neural network models using R
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Deep Learning with TensorFlow 2 and Keras. Regression, ConvNets, GANs, RNNs, NLP, and more with TensorFlow 2 and the Keras API - Second Edition
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Hands-On Machine Learning with Azure. Build powerful models with cognitive machine learning and artificial intelligence
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Jak myślą inteligentne maszyny
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Automatyczna analiza składnikowa języka polskiego
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Deep Learning. Praktyczne wprowadzenie
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Deep Learning. Receptury
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Before Machine Learning Volume 1 - Linear Algebra for A.I. The Fundamental Mathematics for Data Science and Artificial Intelligence
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Machine Learning with R. Expert techniques for predictive modeling to solve all your data analysis problems - Second Edition
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Scala for Machine Learning. Leverage Scala and Machine Learning to construct and study systems that can learn from data
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Moodle Grad
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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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Active Machine Learning with Python. Refine and elevate data quality over quantity with active learning
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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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TinyML Cookbook. Combine machine learning with microcontrollers to solve real-world problems - Second Edition
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Machine Learning Security with Azure. Best practices for assessing, securing, and monitoring Azure Machine Learning workloads
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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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Deep Learning with MXNet Cookbook. Discover an extensive collection of recipes for creating and implementing AI models on MXNet
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Bayesian Analysis with Python. A practical guide to probabilistic modeling - Third Edition
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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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MATLAB for Machine Learning. Unlock the power of deep learning for swift and enhanced results - Second Edition
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MLOps with Red Hat OpenShift. A cloud-native approach to machine learning operations
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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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Deep learning Głęboka rewolucja. Kiedy sztuczna inteligencja spotyka się z ludzką
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Machine Learning with Python. Unlocking AI Potential with Python and Machine Learning
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Deep Learning for Time Series Cookbook. Use PyTorch and Python recipes for forecasting, classification, and anomaly detection
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Machine Learning: Make Your Own Recommender System. Build Your Recommender System with Machine Learning Insights
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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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Accelerate Model Training with PyTorch 2.X. Build more accurate models by boosting the model training process
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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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Privacy-Preserving Machine Learning. A use-case-driven approach to building and protecting ML pipelines from privacy and security threats
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Głębokie uczenie z TensorFlow. Od regresji liniowej po uczenie przez wzmacnianie
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Inżynieria danych na platformie AWS. Jak tworzyć kompletne potoki uczenia maszynowego
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Inteligentna sieć. Algorytmy przyszłości. Wydanie II
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Matematyka dyskretna dla praktyków. Algorytmy i uczenie maszynowe w Pythonie
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Mastering Machine Learning with R. Master machine learning techniques with R to deliver insights for complex projects
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Machine Learning with R. R gives you access to the cutting-edge software you need to prepare data for machine learning. No previous knowledge required – this book will take you methodically through every stage of applying machine learning
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Large Scale Machine Learning with Python. Click here to enter text
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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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Learning Apache Mahout. Acquire practical skills in Big Data Analytics and explore data science with Apache Mahout
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Microsoft Azure Machine Learning. Explore predictive analytics using step-by-step tutorials and build models to make prediction in a jiffy with a few mouse clicks
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R Machine Learning Essentials. Gain quick access to the machine learning concepts and practical applications using the R development environment
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Test-Driven Machine Learning. Control your machine learning algorithms using test-driven development to achieve quantifiable milestones
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Apache Mahout Essentials. Implement top-notch machine learning algorithms for classification, clustering, and recommendations with Apache Mahout
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Learning Bayesian Models with R. Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems
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Mastering Probabilistic Graphical Models Using Python. Master probabilistic graphical models by learning through real-world problems and illustrative code examples in Python
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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 Engineering with Python. Manage the lifecycle of machine learning models using MLOps with practical examples - Second Edition
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De-Mystifying Math and Stats for Machine Learning. Mastering the Fundamentals of Mathematics and Statistics for Machine Learning
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Data Analysis Foundations with Python. Master Data Analysis with Python: From Basics to Advanced Techniques
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Introduction to Algorithms. A Comprehensive Guide for Beginners: Unlocking Computational Thinking
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Deep Learning with TensorFlow and Keras. Build and deploy supervised, unsupervised, deep, and reinforcement learning models - Third Edition
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Quantum Machine Learning and Optimisation in Finance. On the Road to Quantum Advantage
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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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The Kaggle Workbook. Self-learning exercises and valuable insights for Kaggle data science competitions
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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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Aplikacje ChatGPT. Wejdź na wyższy poziom z inteligentnymi programami - generatory, boty i wiele innych!