Uczenie maszynowe
Uczenie maszynowe (ang. machine learning) zajmuje się teorią i praktycznym zastosowaniem algorytmów analizujących dane — stanowi najciekawszą dziedzinę informatyki. Żyjemy w czasach przetwarzania olbrzymiej ilości informacji; za pomocą samouczących się algorytmów będących częścią uczenia maszynowego informacje te są przekształcane w rzeczywistą wiedzę. Dzięki licznym i potężnym bibliotekom o jawnym kodzie źródłowym, które powstały w ostatnich latach, prawdopodobnie teraz jest najlepszy czas, aby zainteresować się uczeniem maszynowym i nauczyć się wykorzystywać potężne algorytmy do wykrywania wzorców w przetwarzanych danych oraz prognozować przyszłe zdarzenia. Przykładami zastosowania Machine Learning są np. mechanizmy wyszukiwarek internetowych, GPS, autokorekta w edytorze tekstu czy boty w komunikatorach.
Jedną z dziedzin uczenia maszynowego jest deep learning, podczas którego komputer uczy się procesów naturalnych dla ludzkiego mózgu (tworzy sieci neuronowe). Technologia ta jest wykorzystywana np. przy identyfikacji głosu i obrazów.
Książki, ebooki, kursy video z kategorii: Uczenie maszynowe dostępne w księgarni Ebookpoint
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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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Natural Language Processing and Computational Linguistics. A practical guide to text analysis with Python, Gensim, spaCy, and Keras
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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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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
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Hands-on Machine Learning with JavaScript. Solve complex computational web problems using machine learning
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Mastering Machine Learning Algorithms. Expert techniques to implement popular machine learning algorithms and fine-tune your models
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Artificial Intelligence for Big Data. Complete guide to automating Big Data solutions using Artificial Intelligence techniques
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Hands-On GUI Programming with C++ and Qt5. Build stunning cross-platform applications and widgets with the most powerful GUI framework
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Machine Learning Solutions. Expert techniques to tackle complex machine learning problems using Python
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Hands-On Automated Machine Learning. A beginner's guide to building automated machine learning systems using AutoML and Python
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Reinforcement Learning with TensorFlow. A beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym
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Deep Learning with TensorFlow. Explore neural networks and build intelligent systems with Python - Second Edition
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Splunk 7 Essentials. Demystify machine data by leveraging datasets, building reports, and sharing powerful insights - Third Edition
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TensorFlow Deep Learning Projects. 10 real-world projects on computer vision, machine translation, chatbots, and reinforcement learning
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TensorFlow: Powerful Predictive Analytics with TensorFlow. Predict valuable insights of your data with TensorFlow
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Deep Learning Quick Reference. Useful hacks for training and optimizing deep neural networks with TensorFlow and Keras
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TensorFlow for Deep Learning. From Linear Regression to Reinforcement Learning
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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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Machine Learning with Swift. Artificial Intelligence for iOS
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Practical Convolutional Neural Networks. Implement advanced deep learning models using Python
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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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Deep Learning with PyTorch. A practical approach to building neural network models using PyTorch
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R Deep Learning Projects. Master the techniques to design and develop neural network models in R
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Practical Computer Vision. Extract insightful information from images using TensorFlow, Keras, and OpenCV
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Scala Machine Learning Projects. Build real-world machine learning and deep learning projects with Scala
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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 and Security. Protecting Systems with Data and Algorithms
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Deep Learning for Computer Vision. Expert techniques to train advanced neural networks using TensorFlow and Keras
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Mastering TensorFlow 1.x. Advanced machine learning and deep learning concepts using TensorFlow 1.x and Keras
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OpenCV 3.x with Python By Example. Make the most of OpenCV and Python to build applications for object recognition and augmented reality - Second Edition
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Computer Vision with OpenCV 3 and Qt5. Build visually appealing, multithreaded, cross-platform computer vision applications
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Cacti Beginner's Guide. Leverage Cacti to design a robust network operations center - Second Edition
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TensorFlow 1.x Deep Learning Cookbook. Over 90 unique recipes to solve artificial-intelligence driven problems with Python
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Statistics for Data Science. Leverage the power of statistics for Data Analysis, Classification, Regression, Machine Learning, and Neural Networks
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Neural Network Programming with Tensorflow. Unleash the power of TensorFlow to train efficient neural networks
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Python Deep Learning Cookbook. Over 75 practical recipes on neural network modeling, reinforcement learning, and transfer learning using Python
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Learning Microsoft Cognitive Services. Leverage Machine Learning APIs to build smart applications - Second Edition
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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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Emotional Intelligence for IT Professionals. The must-have guide for a successful career in IT
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Apache Spark 2.x Machine Learning Cookbook. Over 100 recipes to simplify machine learning model implementations with Spark
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Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow - Second Edition
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Learning TensorFlow. A Guide to Building Deep Learning Systems
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R Deep Learning Cookbook. Solve complex neural net problems with TensorFlow, H2O and MXNet
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Hands-On Deep Learning with TensorFlow. Uncover what is underneath your data!
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Deep Learning with Theano. Perform large-scale numerical and scientific computations efficiently
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Deep Learning. A Practitioner's Approach
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Machine Learning for OpenCV. Intelligent image processing with Python
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Data Science i uczenie maszynowe
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Mastering OpenCV 3. Get hands-on with practical Computer Vision using OpenCV 3 - Second Edition
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Python Deep Learning. Next generation techniques to revolutionize computer vision, AI, speech and data analysis
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Deep Learning with Keras. Implementing deep learning models and neural networks with the power of Python
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Deep Learning with TensorFlow. Explore neural networks with Python
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Learning Microsoft Cognitive Services. Click here to enter text
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TensorFlow Machine Learning Cookbook. Over 60 practical recipes to help you master Google’s TensorFlow machine learning library
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OpenCV 3 Computer Vision Application Programming Cookbook. Recipes to make your applications see - Third Edition
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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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Practical Machine Learning with H2O. Powerful, Scalable Techniques for Deep Learning and AI
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Introduction to Machine Learning with Python. A Guide for Data Scientists
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Python: Deeper Insights into Machine Learning. Deeper Insights into Machine Learning
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Large Scale Machine Learning with Python. Click here to enter text
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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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Mastering Machine Learning with R. Master machine learning techniques with R to deliver insights for complex projects
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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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Machine Learning with R. Expert techniques for predictive modeling to solve all your data analysis problems - Second Edition
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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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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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Learning Apache Mahout. Acquire practical skills in Big Data Analytics and explore data science with Apache Mahout
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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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R Machine Learning Essentials. Gain quick access to the machine learning concepts and practical applications using the R development environment
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Thoughtful Machine Learning. A Test-Driven Approach
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Practical Machine Learning: Innovations in Recommendation
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Practical Machine Learning: A New Look at Anomaly Detection
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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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Natural Language Annotation for Machine Learning
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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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Designing Data Visualizations. Representing Informational Relationships