11. Building an Artificial Intelligence Algorithm
We will start this chapter by introducing the most basic form of machine learning model: the linear regression model. We will use batch gradient descent in NumPy to train a regression model. Then we will get started with the popular deep learning framework PyTorch. Toward the end of the chapter, we will delve into one of the most exciting fields in deep learning research: reinforcement learning, specifically the deep Q-learning algorithm. Lastly, we will learn how to build a deep Q-learning algorithm to solve classic reinforcement learning problems, and we will learn how to improve the algorithm by implementing a double deep Q-learning algorithm in an activity.
By the end of this chapter, you will have a comprehensive understanding of how an Artificial Intelligence (AI) algorithm is built and trained with different implementations such as NumPy and PyTorch. Both NumPy and PyTorch are Python-based scientific...