Piotr Szajowski - książki
Tytuły autora: dostępne w księgarni Ebookpoint
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Dylemat sztucznej inteligencji. 7 zasad odpowiedzialnego tworzenia technologii
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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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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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Deep Learning with MXNet Cookbook. Discover an extensive collection of recipes for creating and implementing AI models on MXNet
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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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TensorFlow Developer Certificate Guide. Efficiently tackle deep learning and ML problems to ace the Developer Certificate exam
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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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Przetwarzanie języka naturalnego w praktyce. Przewodnik po budowie rzeczywistych systemów NLP
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Zaufanie do systemów sztucznej inteligencji
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The Kaggle Workbook. Self-learning exercises and valuable insights for Kaggle data science competitions
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Uczenie maszynowe. Elementy matematyki w analizie danych
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Practicing Trustworthy Machine Learning
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Praktyczne uczenie maszynowe w języku R
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Hands-On Healthcare Data
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Głębokie uczenie. Wprowadzenie
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Machine Learning at Scale with H2O. A practical guide to building and deploying machine learning models on enterprise systems
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Deep learning z TensorFlow 2 i Keras dla zaawansowanych. Sieci GAN i VAE, deep RL, uczenie nienadzorowane, wykrywanie i segmentacja obiektów i nie tylko. Wydanie II
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Natural Language Processing with Transformers, Revised Edition
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Deep Learning with PyTorch Lightning. Swiftly build high-performance Artificial Intelligence (AI) models using Python
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Democratizing Artificial Intelligence with UiPath. Expand automation in your organization to achieve operational efficiency and high performance
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Distributed Machine Learning with Python. Accelerating model training and serving with distributed systems
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Essential Mathematics for Quantum Computing. A beginner's guide to just the math you need without needless complexities
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The Kaggle Book. Data analysis and machine learning for competitive data science
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TinyML. Wykorzystanie TensorFlow Lite do uczenia maszynowego na Arduino i innych mikrokontrolerach
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Matematyka dyskretna dla praktyków. Algorytmy i uczenie maszynowe w Pythonie
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Agile Machine Learning with DataRobot. Automate each step of the machine learning life cycle, from understanding problems to delivering value
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The TensorFlow Workshop. A hands-on guide to building deep learning models from scratch using real-world datasets
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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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Conversational AI with Rasa. Build, test, and deploy AI-powered, enterprise-grade virtual assistants and chatbots
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Practical Weak Supervision
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Deep learning dla programistów. Budowanie aplikacji AI za pomocą fastai i PyTorch
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Automated Machine Learning with Microsoft Azure. Build highly accurate and scalable end-to-end AI solutions with Azure AutoML
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AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide. The definitive guide to passing the MLS-C01 exam on the very first attempt
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Przetwarzanie języka naturalnego w akcji
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Machine Learning Using TensorFlow Cookbook. Create powerful machine learning algorithms with TensorFlow
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Odsłaniamy SQL Server 2019: Klastry Big Data i uczenie maszynowe
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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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The Natural Language Processing Workshop. Confidently design and build your own NLP projects with this easy-to-understand practical guide
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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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Hands-On Mathematics for Deep Learning. Build a solid mathematical foundation for training efficient deep neural networks
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Uczenie głębokie od zera. Podstawy implementacji w Pythonie
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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 Deep Learning with R. A practical guide to designing, building, and improving neural network models using R
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Przetwarzanie i analiza obrazów w systemach przemysłowych. Wybrane zastosowania
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Automatyczna analiza składnikowa języka polskiego
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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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TinyML. Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
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Practical Automated Machine Learning on Azure. Using Azure Machine Learning to Quickly Build AI Solutions
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Deep Learning
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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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Practical Machine Learning with R. Define, build, and evaluate machine learning models for real-world applications
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Deep Learning. Receptury
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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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Deep learning Głęboka rewolucja. Kiedy sztuczna inteligencja spotyka się z ludzką
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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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Applied Deep Learning with Keras. Solve complex real-life problems with the simplicity of Keras
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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide. A practical guide to building neural networks using Microsoft's open source deep learning framework
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Generative Adversarial Networks Projects. Build next-generation generative models using TensorFlow and Keras
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Python w uczeniu maszynowym
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Computer Vision Projects with OpenCV and Python 3. Six end-to-end projects built using machine learning with OpenCV, Python, and TensorFlow
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Go Machine Learning Projects. Eight projects demonstrating end-to-end machine learning and predictive analytics applications in Go
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Advanced Deep Learning with Keras. Apply deep learning techniques, autoencoders, GANs, variational autoencoders, deep reinforcement learning, policy gradients, and more
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Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems
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Python Reinforcement Learning Projects. Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow
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R Deep Learning Essentials. A step-by-step guide to building deep learning models using TensorFlow, Keras, and MXNet - Second Edition
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Building Machine Learning Systems with Python. Explore machine learning and deep learning techniques for building intelligent systems using scikit-learn and TensorFlow - Third Edition
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Hands-On Deep Learning for Images with TensorFlow. Build intelligent computer vision applications using TensorFlow and Keras
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Hands-On Natural Language Processing with Python. A practical guide to applying deep learning architectures to your NLP applications
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Machine Learning with Core ML. An iOS developer's guide to implementing machine learning in mobile apps
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Deep Learning Cookbook. Practical Recipes to Get Started Quickly
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Deep Learning By Example. A hands-on guide to implementing advanced machine learning algorithms and neural networks
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Building Smart Drones with ESP8266 and Arduino. Build exciting drones by leveraging the capabilities of Arduino and ESP8266
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Practical Convolutional Neural Networks. Implement advanced deep learning models using Python
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Deep Learning Essentials. Your hands-on guide to the fundamentals of deep learning and neural network modeling
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Machine Learning with R Cookbook. Analyze data and build predictive models - Second Edition
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Neural Networks with R. Build smart systems by implementing popular deep learning models in R
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Machine Learning With Go. Implement Regression, Classification, Clustering, Time-series Models, Neural Networks, and More using the Go Programming Language
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Inteligentna sieć. Algorytmy przyszłości. Wydanie II
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Deep Learning with TensorFlow. Explore neural networks with Python
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Windows Server 2016 Hyper-V Cookbook. Save time and resources by getting to know the best practices and intelligence from industry experts - Second Edition
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Thoughtful Machine Learning with Python. A Test-Driven Approach
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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 Apache Mahout. Acquire practical skills in Big Data Analytics and explore data science with Apache Mahout
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Uczenie maszynowe dla programistów
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Thoughtful Machine Learning. A Test-Driven Approach
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Machine Learning for Hackers. Case Studies and Algorithms to Get You Started
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Machine Learning for Email. Spam Filtering and Priority Inbox
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Konwolucyjne sieci neuronowe. Kurs video. Tensorflow i Keras w rozpoznawaniu obrazów
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Machine Learning i język Python. Kurs video. Praktyczne wykorzystanie popularnych bibliotek
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Applied Deep Learning on Graphs. Leveraging Graph Data to Generate Impact Using Specialized Deep Learning Architectures
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Deep learning Głęboka rewolucja. Kiedy sztuczna inteligencja spotyka się z ludzką
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Building Machine Learning Systems with Python
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Machine Learning with R Cookbook