Uczenie maszynowe stanowi jeden z najbardziej fascynujących i dynamicznie rozwijających się obszarów technologii informatycznej. W księgarni internetowej helion.pl oferujemy szeroki zakres książek oraz kursów video, które pomogą Ci zgłębić tajniki tej dziedziny.
Uczenie maszynowe
Książki, ebooki, kursy video z kategorii: Uczenie maszynowe dostępne w księgarni Helion
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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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Building Machine Learning Powered Applications. Going from Idea to Product
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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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TinyML. Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers
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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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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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Java Deep Learning Cookbook. Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j
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Google BigQuery: The Definitive Guide. Data Warehousing, Analytics, and Machine Learning at Scale
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Practical Automated Machine Learning on Azure. Using Azure Machine Learning to Quickly Build AI Solutions
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Practical Time Series Analysis. Prediction with Statistics and Machine Learning
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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 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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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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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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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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Mastering OpenCV 4 with Python. A practical guide covering topics from image processing, augmented reality to deep learning with OpenCV 4 and Python 3.7
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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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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 Algorithmic Trading. Design and implement investment strategies based on smart algorithms that learn from data using Python
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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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Hands-On Artificial Intelligence for Beginners. An introduction to AI concepts, algorithms, and their implementation
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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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CompTIA Security+ Certification Guide. Master IT security essentials and exam topics for CompTIA Security+ SY0-501 certification
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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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Applied Data Visualization with R and ggplot2. Create useful, elaborate, and visually appealing plots
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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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Machine Learning Algorithms. Popular algorithms for data science and machine learning - Second Edition
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Hands-On Convolutional Neural Networks with TensorFlow. Solve computer vision problems with modeling in TensorFlow and Python
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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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Hands-On Intelligent Agents with OpenAI Gym. Your guide to developing AI agents using deep reinforcement learning
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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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Apache Spark Deep Learning Cookbook. Over 80 best practice recipes for the distributed training and deployment of neural networks using Keras and TensorFlow
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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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Machine Learning with Core ML. An iOS developer's guide to implementing machine learning in mobile apps
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Mastering Machine Learning for Penetration Testing. Develop an extensive skill set to break self-learning systems using Python
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Deep Learning Cookbook. Practical Recipes to Get Started Quickly
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Beginning Swift. Master the fundamentals of programming in Swift 4
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Hands-On Data Science with Anaconda. Utilize the right mix of tools to create high-performance data science applications
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Natural Language Processing with TensorFlow. Teach language to machines using Python's deep learning library
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Google Cloud AI Services Quick Start Guide. Build intelligent applications with Google Cloud AI services
Jakie książki pozwolą na praktyczną naukę uczenia maszynowego?
Zastanawiasz się czym jest Uczenie Maszynowe (Machine Learning)? To technika programowania komputerów, które uczą się wykonywać określone zadania na podstawie ogromnych ilości zebranych danych. W wielu przypadkach to rozwiązanie sprawdza się znacznie lepiej niż tradycyjne metody programowania, szczególnie w obszarach, gdzie trudno jest sformułować jasne reguły decyzyjne. Jeśli szukasz praktycznych przykładów uczenia maszynowego, to książki z tej kategorii oferują wiele case studies i analiz. Nasza oferta obejmuje różnorodne książki, które skupiają się na wszystkich najważniejszych aspektach uczenia maszynowego.
Uczenie maszynowe jak zacząć? – książki dla początkujących
Jeśli dopiero zaczynasz swoją przygodę z tą dziedziną, polecamy książkę "Jak projektować systemy uczenia maszynowego”, która omawia temat uczenia maszynowego od podstaw. Znajdziesz tu także praktyczne poradniki, takie jak "Uczenie maszynowe dla programistów" czy „Uczenie głębokie od zera”, które krok po kroku pokażą Ci, jak zacząć przygodę z uczeniem maszynowym czy uczeniem głębokim. Książki te sprawnie wprowadzą Cię także w zagadnienia związane z metodami uczenia nadzorowanego i nienadzorowanego, omówią kluczowe algorytmy i dostarczą liczne przykłady uczenia maszynowego.
Uczenie maszynowe i Python: książki dla programistów
Jeśli Twoim językiem programowania jest Python, to mamy dla Ciebie wiele propozycji książek. Język ten idealnie nadaje się do programowania mechanizmów uczenia maszynowego. Znajdziesz tu takie książki jak „Uczenie maszynowe w Pythonie. Receptury” oraz „Machine learning, Python i data science. Wprowadzenie” czy „Uczenie maszynowe z użyciem Scikit-Learn, Keras i TensorFlow”, dzięki którym dowiesz się jak korzystać z bibliotek takich jak scikit-learn czy TensorFlow, by efektywnie budować i trenować inteligentne modele.
Uczenie maszynowe a sztuczna inteligencja: książki dla zaawansowanych
Różnica między uczeniem maszynowym a sztuczną inteligencją jest często niejasna. W skrócie, sztuczna inteligencja to szeroki obszar informatyki skupiający się na tworzeniu inteligentnych systemów i maszyn, podczas gdy uczenie maszynowe to jedna z technik stosowanych w AI. Wiele osób interesuje się również sieciami neuronowymi, które stanowią podstawę dla głębokiego uczenia maszynowego - jednego z najgorętszych tematów w dziedzinie AI.
W naszej ofercie znajdziesz również książki opisujące różne algorytmy uczenia maszynowego, w tym drzewa decyzyjne, oraz metody uczenia maszynowego, takie jak uczenie nienadzorowane,
Nie ważne, czy jesteś początkującym entuzjastą czy doświadczonym programistą, nasza oferta obejmuje książki dla każdego. A jeśli preferujesz materiały w formie elektronicznej, nie zapomnij sprawdzić naszych książek w formacie PDF, EPUB czy MOBI.
Zachęcamy do odkrywania świata uczenia maszynowego poprzez nasze książki, które rozwijają umiejętności i otwierają drzwi do nowoczesnej analizy danych i sztucznej inteligencji.