pstrongStart with the basics of reinforcement learning and explore deep learning concepts such as deep Q-learning, deep recurrent Q-networks, and policy-based methods with this practical guidestrongppstrongKey Featuresstrongp ul liUse TensorFlow to write reinforcement learning agents for performing challenging tasksli liLearn how to solve finite Markov decision problemsli liTrain models to understand popular video games like Breakoutli ul pstrongBook Descriptionstrongp pVarious intelligent applications such as video games, inventory management software, warehouse robots, and translation tools use reinforcement learning RL to make decisions and perform actions that maximize the probability of the desired outcome. This book will help you to get to grips with the techniques and the algorithms for implementing RL in your machine learning models.p pStarting with an introduction to RL, you'll be guided through different RL environments and frameworks. You'll learn how to implement your own c