deep reinforcement learning python (149 Ergebnisse)

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Bündel. Zustand: Neu. Neuware - - Grundlegende Konzepte und Terminologie- Praktischer Einsatz mit PyTorch- Projekte umsetzenDieses Buch zeigt Ihnen, wie Sie Agenten programmieren, die basierend auf direktem Feedback aus ihrer Umgebung selbstständig lernen und sich dabei verbessern. Sie werden Netzwerke mit dem beliebten PyTorch-Deep-Learning-Framework aufbauen, um bestärkende Lernalgorithmen zu erforschen. Diese reichen von Deep-Q-Networks über Methoden zur Gradientenmethode bis hin zu evolutionären Algorithmen.Im weiteren Verlauf des Buches wenden Sie Ihre Kenntnisse in praktischen Projekten wie der Steuerung simulierter Roboter, der Automatisierung von Börsengeschäften oder dem Aufbau eines Spiel-Bots an.Aus dem Inhalt:- Strukturierungsprobleme als Markov-Entscheidungsprozesse- Beliebte Algorithmen wie Deep Q-Networks, Policy Gradient-Methode und Evolutionäre Algorithmen und die Intuitionen, die sie antreiben- Anwendung von Verstärkungslernalgorithmen auf reale ProblemeEXTRA: Elektronisches Buch insideSystemvoraussetzungen für Elektronisches Buch inside: Internet-Verbindung und Adobe-Reader oder Elektronisches Buch-Reader bzw. Adobe Digital Editions.

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Paperback or Softback. Zustand: New. Python AI Programming: Navigating fundamentals of ML, deep learning, NLP, and reinforcement learning in practice 0.73. Book.

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paperback. Zustand: New. Language:Chinese.Paperback.Pub Date:2022-06-01 Pages:320 Publisher:China Water Resources and Hydropower Press Deep Learning Practice: Computer Vision Development and Application Based on TensorFlow 2.X starts from the construction of the environment and the basic grammar of TensorFlow 2.X . and gradually go deep into the theory and practical application of algorithm models in the field of computer vision. and focus on how to use the TensorFlow 2.X framework to implement various classic deep l.

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paperback. Zustand: New. Language:Chinese.Paperback.Pub Date:2022-06-01 Pages:448 Publisher:China Water Resources and Hydropower Press Machine Learning Deep Learning Image Recognition from Basics to Case Practice introduces the field of artificial intelligence with a large number of graphics and images combined with Python code Knowledge about image recognition. The book consists of 3 parts. of which the first part introduces the basic knowledge and the use of related tools such as Python. Jupyter Nobebook and NumPy.

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paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2022-11-01 Pages: 244 Publisher: Tsinghua University Press This book focuses on the basic concepts of deep reinforcement learning theory. cutting-edge basic theory and Python application implementation. First introduce the basics of Markov decision-making. model-based algorithms. model-free methods. dynamic programming. Monte Carlo. and function approximation; then elaborate on algorithms such as reinforcement learning. deep reinforcement learning. and mu.

paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2022-07-01 Pages: 298 Publisher: China Water Conservancy and Hydropower Publishing House Intelligent Recommendation System Development Practice is written based on Python 3.7. The whole book focuses on the development practice of the recommendation model. and introduces various types of recommendations for readers. The development process of the model and its application in various business scenarios. The book is divided into 4 parts. The first part brief.

paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2022-09-01 Pages: 340 Publisher: China Water Conservancy and Hydropower Press Deep learning is one of the most popular fields of artificial intelligence. Methods of implementing various algorithms. and the mathematics behind the algorithms. The book is divided into 3 parts with a total of 11 chapters. of which the first part introduces the relevant knowledge of getting started with deep learning. how to build your own neural network. and how to use Python.

paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2021-10-01 Pages: 308 Publisher: Machinery Industry Press Deep Reinforcement Learning combines deep learning and reinforcement learning. enabling artificial intelligence to learn how to solve sequential decision problems without supervision.?In the past ten years. deep reinforcement learning has achieved remarkable results on a series of problems. covering everything from single-player and multiplayer games to robotics.?This book adopts the method of comb.

paperback. Zustand: New. Paperback. Pub Date: 2019-01-01 Pages: 203 Language: Chinese Publisher: Mechanical Industry Press Reinforcement learning is an important machine learning method. and has many applications in the fields of agent and analysis and prediction. Python Intensive Learning Practice: Applying OpenAI Gym and TensorFlow to Master Reinforcement Learning and.

paperback. Zustand: New. Paperback.Pub Date:2024-01 Pages:184 Publisher:China Water Conservancy and Hydropower Press As the first artificial intelligence robot AlphaGo to defeat the world champion of Go. we know that its main working principle is deep learning. With the successive releases of AlphaGo Zero and Alpha Zero. reinforcement learning. one of the classic algorithms of machine learning. has received more attention in the field of artificial intelligence. Introduction to Reinforcement Learning Algorithms uses .

paperback. Zustand: New. Paperback. Pub Date: 2018-06-01 Pages: 260 Publisher: Mechanical Industry Press. Python Deep Learning: 75 Solutions for Neural Network Modeling. Reinforced Learning and Migration Learning from top to bottom and from bottom to bottom And the method to show deep learning solutions for practical problems in different fields. including image recognition. natural language processing.

paperback. Zustand: New. Language:Chinese.Paperback. Pub Date: 2020-12-01 Pages: 396 Publisher: Machinery Industry Press This book is aimed at computer science college students and software engineers.?This course aims to introduce deep reinforcement learning without prior knowledge of related topics.?However. we assume that the reader has a basic understanding of machine learning and deep learning. and an intermediate understanding of Python programming.?Some experience using PyTorch is also useful. but not required.

paperback. Zustand: New. Paperback. Pub Date: 2019-01-01 Publisher: Mechanical Industry Press Python 3.6 Programming Practice Guide-Introduction to Computer Science (the third edition of the original book) introduces the basic knowledge of programming through the Python language. including modern programming Various data storage and basic processing methods commonly used in languages. such as numerical values. strings. lists. sets. dictionaries. and text information; program conditions and loop control structures; fu.

Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Le 'Deep Reinforcement Learning' est appliqué à la stratégie de connectivité 5G. Des simulations python sur l'alignement de faisceaux sont présentées (librairies Scikitlearn et Keras). Le 'Reinforcement Learning' (RL) est une technique d'apprentissage statistique par renforcement basé sur des actions et des récompenses, avec exploration des arbres de possibilités. Il améliore l'algorithme Minimax inventé par C. Shannon en 1949 appliqué au jeu d'échecs contre ordinateur. Le RL calcule également le chemin de sortie d'un labyrinthe.Si l'espace des états-actions est très grand, le 'Deep Reinforcement Learning' (DRL) est utilisé. C'est une amélioration du RL par un réseau de neurones, permettant la prise de décision locale en n'ayant qu'une information parcellaire (problème distribué).Le DRL, outil universel, peut résoudre les questions d'optimisation non convexe. -C'est l'objet de la première partie.-La seconde partie détaille des applications aux télécommunications sans fils comme l'alignement de faisceaux. Dans le cadre des jeux et de la gestion de réseaux en téléphonie 5G, des problèmes de prise de décision et d'optimisation séquentiels sont posés.