Uczenie maszynowe - książki
Książki, ebooki, kursy video z kategorii: Uczenie maszynowe dostępne w księgarni Helion
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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 Simulation Modeling with Python. Develop simulation models to get accurate results and enhance decision-making processes
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Data Science and Machine Learning Interview Questions Using R
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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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The Today and Future of WSN, AI, and IoT
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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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Data Science for Business Professionals
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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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Pragmatic Machine Learning with Python
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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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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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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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Przetwarzanie i analiza obrazów w systemach przemysłowych. Wybrane zastosowania
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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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Automatyczna analiza składnikowa języka polskiego
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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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Deep Learning with R Cookbook. Over 45 unique recipes to delve into neural network techniques using R 3.5.x
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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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Python Feature Engineering Cookbook. Over 70 recipes for creating, engineering, and transforming features to build machine learning models
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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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Advanced Deep Learning with R. Become an expert at designing, building, and improving advanced neural network models using R
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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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Dancing with Qubits. How quantum computing works and how it can change the world
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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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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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Practical Time Series Analysis. Prediction with Statistics and Machine Learning
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Programming PyTorch for Deep Learning. Creating and Deploying Deep Learning Applications
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Practical Data Science with SAP. Machine Learning Techniques for Enterprise Data
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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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Hands-On Deep Learning with Go. A practical guide to building and implementing neural network models using Go
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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 Ensemble Learning with Python. Build highly optimized ensemble machine learning models using scikit-learn and Keras
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Hands-On Deep Learning for IoT. Train neural network models to develop intelligent IoT applications
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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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Machine Learning for Finance. Principles and practice for financial insiders
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Supervised Machine Learning with Python. Develop rich Python coding practices while exploring supervised machine learning
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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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Advanced Machine Learning with R. Tackle data analytics and machine learning challenges and build complex applications with R 3.5
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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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Applied Deep Learning with Keras. Solve complex real-life problems with the simplicity of Keras
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Hands-On Q-Learning with Python. Practical Q-learning with OpenAI Gym, Keras, and TensorFlow
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Machine Learning with R. Expert techniques for predictive modeling - Third Edition
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TensorFlow Reinforcement Learning Quick Start Guide. Get up and running with training and deploying intelligent, self-learning agents using Python
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Hands-On Neural Networks with Keras. Design and create neural networks using deep learning and artificial intelligence principles
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Python Machine Learning Cookbook. Over 100 recipes to progress from smart data analytics to deep learning using real-world datasets - Second Edition
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Hands-On Machine Learning with IBM Watson. Leverage IBM Watson to implement machine learning techniques and algorithms using Python
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TensorFlow 2.0 Quick Start Guide. Get up to speed with the newly introduced features of TensorFlow 2.0
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Machine Learning with R Quick Start Guide. A beginner's guide to implementing machine learning techniques from scratch using R 3.5
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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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Applied Unsupervised Learning with R. Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA
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Neural Network Projects with Python. The ultimate guide to using Python to explore the true power of neural networks through six projects
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Python Machine Learning By Example. Implement machine learning algorithms and techniques to build intelligent systems - Second Edition
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Neural Networks with Keras Cookbook. Over 70 recipes leveraging deep learning techniques across image, text, audio, and game bots
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Hands-On Unsupervised Learning with Python. Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more
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The Enterprise Big Data Lake. Delivering the Promise of Big Data and Data Science
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Hands-On Java Deep Learning for Computer Vision. Implement machine learning and neural network methodologies to perform computer vision-related tasks
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Ensemble Machine Learning Cookbook. Over 35 practical recipes to explore ensemble machine learning techniques using Python
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Machine Learning with the Elastic Stack. Expert techniques to integrate machine learning with distributed search and analytics
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Mastering Machine Learning with R. Advanced machine learning techniques for building smart applications with R 3.5 - Third Edition
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Generative Adversarial Networks Projects. Build next-generation generative models using TensorFlow and Keras
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Machine Learning Quick Reference. Quick and essential machine learning hacks for training smart data models
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Python Machine Learning Blueprints. Put your machine learning concepts to the test by developing real-world smart projects - Second Edition
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Intelligent Projects Using Python. 9 real-world AI projects leveraging machine learning and deep learning with TensorFlow and Keras
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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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R Machine Learning Projects. Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5
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Generative Adversarial Networks Cookbook. Over 100 recipes to build generative models using Python, TensorFlow, and Keras
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Hands-On Machine Learning for Cybersecurity. Safeguard your system by making your machines intelligent using the Python ecosystem
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Hands-On Meta Learning with Python. Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow
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Keras 2.x Projects. 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras
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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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Deep Learning with PyTorch Quick Start Guide. Learn to train and deploy neural network models in Python
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Python: Advanced Guide to Artificial Intelligence. Expert machine learning systems and intelligent agents using Python
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Artificial Intelligence and Machine Learning Fundamentals. Develop real-world applications powered by the latest AI advances
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Practical Site Reliability Engineering. Automate the process of designing, developing, and delivering highly reliable apps and services with SRE
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Hands-On Data Science with R. Techniques to perform data manipulation and mining to build smart analytical models using R
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TensorFlow Machine Learning Projects. Build 13 real-world projects with advanced numerical computations using the Python ecosystem
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Recurrent Neural Networks with Python Quick Start Guide. Sequential learning and language modeling with 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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Machine Learning in Java. Helpful techniques to design, build, and deploy powerful machine learning applications in Java - Second Edition
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Keras Deep Learning Cookbook. Over 30 recipes for implementing deep neural networks in Python
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Data Science Algorithms in a Week. Top 7 algorithms for scientific computing, data analysis, and machine learning - 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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Python Deep Learning Projects. 9 projects demystifying neural network and deep learning models for building intelligent systems
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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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Machine Learning Projects for Mobile Applications. Build Android and iOS applications using TensorFlow Lite and Core ML
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Machine Learning for Healthcare Analytics Projects. Build smart AI applications using neural network methodologies across the healthcare vertical market
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Machine Learning with scikit-learn Quick Start Guide. Classification, regression, and clustering techniques in Python
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IBM Watson Projects. Eight exciting projects that put artificial intelligence into practice for optimal business performance
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Hands-On Neural Network Programming with C#. Add powerful neural network capabilities to your C# enterprise applications
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Python Reinforcement Learning Projects. Eight hands-on projects exploring reinforcement learning algorithms using TensorFlow
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Keras Reinforcement Learning Projects. 9 projects exploring popular reinforcement learning techniques to build self-learning agents
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Mastering Arduino. A project-based approach to electronics, circuits, and programming
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CompTIA Project+ Certification Guide. Learn project management best practices and successfully pass the CompTIA Project+ PK0-004 exam
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Hands-On Markov Models with Python. Implement probabilistic models for learning complex data sequences using the Python ecosystem
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Learning Microsoft Cognitive Services. Use Cognitive Services APIs to add AI capabilities to your applications - Third Edition
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R Programming Fundamentals. Deal with data using various modeling techniques
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Hands-On Artificial Intelligence with Java for Beginners. Build intelligent apps using machine learning and deep learning with Deeplearning4j
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Hands-On Transfer Learning with Python. Implement advanced deep learning and neural network models using TensorFlow and Keras
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TensorFlow Machine Learning Cookbook. Over 60 recipes to build intelligent machine learning systems with the power of Python - Second Edition
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Artificial Intelligence for Robotics. Build intelligent robots that perform human tasks using AI techniques
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Hands-On Artificial Intelligence for Search. Building intelligent applications and perform enterprise searches
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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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Hands-On Deep Learning for Images with TensorFlow. Build intelligent computer vision applications using TensorFlow and Keras
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Python Artificial Intelligence Projects for Beginners. Get up and running with Artificial Intelligence using 8 smart and exciting AI applications
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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 Ensemble Learning with R. A beginner's guide to combining the power of machine learning algorithms using ensemble techniques
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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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Hands-On Computer Vision with Julia. Build complex applications with advanced Julia packages for image processing, neural networks, and Artificial Intelligence
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Java Deep Learning Projects. Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs
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Natural Language Processing and Computational Linguistics. A practical guide to text analysis with Python, Gensim, spaCy, and Keras
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Hands-On Reinforcement Learning with Python. Master reinforcement and deep reinforcement learning using OpenAI Gym and TensorFlow
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Mastering Machine Learning for Penetration Testing. Develop an extensive skill set to break self-learning systems using Python
