01621nam a22002057a 4500 20250211111741.0 250211b ||||| |||| 00| 0 eng d 9781484294055 AL eng 23 332 AHLR Ahlawat Samit 198943 Reinforcement learning for finance : solve problems in finance with CNN and RNN using the tensorflow library New York Apress 2023 xv,423p PB 23x15cm. Genral 6391 ₹959.20 ₹ ₹1199.00 20% 6/02/2025 This book introduces reinforcement learning with mathematical theory and practical examples from quantitative finance using the TensorFlow library Reinforcement Learning for Finance begins by describing methods for training neural networks. Next, it discusses CNN and RNN – two kinds of neural networks used as deep learning networks in reinforcement learning. Further, the book dives into reinforcement learning theory, explaining the Markov decision process, value function, policy, and policy gradients, with their mathematical formulations and learning algorithms. It covers recent reinforcement learning algorithms from double deep-Q networks to twin-delayed deep deterministic policy gradients and generative adversarial networks with examples using the TensorFlow Python library. It also serves as a quick hands-on guide to TensorFlow programming, covering concepts ranging from variables and graphs to automatic differentiation, layers, models, andloss functions. Economics Financial Economics 198944 ddc BK 233747 233747 0 0 ddc 0 0 MCOM SACPG SACPG 2025-02-08 Biblios Book Point 959.20 0 332 AHLR PG024845 2025-02-11 00:00:00 1199.00 2025-02-11 BK