Call Number (LC) | Title | Results |
---|---|---|
Q325.5 .Z56 2021 | Machine learning / | 1 |
Q325.5 .Z59 2020 | Text mining with machine learning : principles and techniques / | 1 |
Q325.5 ǂb K36 2009eb | ||
Q325.5 ebook |
Machine learning y deep learning : usando Python, Scikit y Keras / Ciberseguridad : un enfoque desde la ciencia de datos / |
2 |
Q325.6 |
Reinforcement learning algorithms with Python : learn, understand, and develop smart algorithms for addressing AI challenges / The art of reinforcement learning : fundamentals, mathematics, and implementations with Python / Integral and inverse reinforcement learning for optimal control systems and games / Exploiting environment configurability in reinforcement learning / Fundamentals of reinforcement learning / Reinforcement learning for reconfigurable intelligent surfaces : assisted wireless communication systems / Reinforcement learning : theory and python implementation / Reinforcement learning in motion / Deep reinforcement learning fundamentals, research and applications / Statistical reinforcement learning : modern machine learning approaches / Multi-agent machine learning : a reinforcement approach / Reinforcement learning with hybrid quantum approximation in the NISQ context / Reinforcement learning for cyber-physical systems with cybersecurity case studies / Deep reinforcement learning with Python with Pytorch, Tensorflow and OpenAI Gym / Reinforcement learning algorithms analysis and applications / Learn Python in five minutes with Colab Notebook. Applied reinforcement learning with Python : with OpenAI Gym, Tensorflow and Keras / Hands-on reinforcement learning for games : implementing self-learning agents in games using artificial intelligence techniques / Hands-on Q-learning with Python : practical Q-learning with OpenAI Gym, Keras, and TensorFlow / Making reinforcement learning practical for real-world developers / Reinforcement learning and deep RL Python (theory and projects). Deep reinforcement learning with Python : with Pytorch, Tensorflow and OpenAI Gym / A friendly introduction to deep reinforcement learning and policy gradients. Reinforcement Learning : Optimal Feedback Control with Industrial Applications / Reinforcement learning for optimal feedback control : a Lyapunov-based approach / Reinforcement learning and approximate dynamic programming for feedback control / Learning motor skills : from algorithms to robot experiments / Multi-Agent Coordination A Reinforcement Learning Approach. Reinforcement learning : with Open AI, TensorFlow and Keras using Python / Reinforcement learning with TensorFlow : a beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym / Keras reinforcement learning projects : 9 projects exploring popular reinforcement learning techniques to build self-learning agents / Reinforcement Learning (RL) in Python. Keras 2.x projects : 9 projects demonstrating faster experimentation of neural network and deep learning applications using Keras / Training a reinforcement learning agent to play soccer (football). Hands-on deep learning for games : leverage the power of neural networks and reinforcement learning to build intelligent games / TensorFlow reinforcement learning quick start guide : get up and running with training and deploying intelligent, self-learning agents using Python / Reinforcement learning from scratch : understanding current approaches -- with examples in Java and Greenfoot / Applied reinforcement learning with Python with OpenAI Gym, Tensorflow and Keras / Generic multi-agent reinforcement learning approach for flexible job-shop scheduling / Deep reinforcement learning / Reinforcement learning for sequential decision and optimal control / Kyōka gakushū hen / REINFORCEMENT LEARNING FOR FINANCE a python-based introduction / |
51 |
Q325.6 .A45 2023 | Reinforcement learning for finance : solve problems in finance with CNN and RNN using the TensorFlow library / | 2 |
Q325.6 .B45 2023 | Distributional reinforcement learning / | 2 |
Q325.6 .D44 2020eb | Deep reinforcement learning : fundamentals, research and applications / | 1 |
Q325.6 .D888 2018eb | Reinforcement Learning with TensorFlow : a beginner's guide to designing self-learning systems with TensorFlow and OpenAI Gym. | 1 |
Q325.6 .E87 2008eb | Recent advances in reinforcement learning 8th European workshop, EWRL 2008, Villeneuve d'Ascq, France, June 30-July 3, 2008 : revised and selected papers / | 1 |
Q325.6 .E97 2011 | Recent advances in reinforcement Learning 9th European Workshop, EWRL 2011, Athens, Greece, September 9-11, 2011, Revised selected papers / | 1 |
Q325.6 .E97 2024eb | Explainable agency in artificial intelligence : research and practice / | 1 |
Q325.6 .F76 2010 | Qualitative spatial abstraction in reinforcement learning | 1 |
Q325.6 .G388 2015eb | Design of experiments for reinforcement learning / | 1 |
Q325.6 .H36 2021 | Handbook of reinforcement learning and control / | 1 |
Q325.6 .H47 2013 | TEXPLORE temporal difference reinforcement learning for robots and time-constrained domains / | 1 |
Q325.6 .H82 2023 | The art of reinforcement learning : fundamentals, mathematics, and implementations with Python / | 3 |
Q325.6 .K85 2012 |
Reinforcement and systemic machine learning for decision making Reinforcement and systemic machine learning for decision making / |
3 |
Q325.6 .L53 2019 | Reinforcement learning for cyber-physical systems with cybersecurity case studies / | 1 |
Q325.6 .M49 2022 | Control systems and reinforcement learning / | 1 |