Vectorization with JAX

Vectorization is a fundamental technique for achieving efficient numerical computations, especially when dealing with large datasets or complex mathematical operations. This chapter explores how JAX leverages vectorization to optimize performance and streamline code execution.

Readers will gain an understanding of how to use JAX's vmap function to apply operations over arrays without the need for explicit loops, thereby enhancing computational efficiency. We'll discuss the advantages of vectorized operations, such as improved speed and scalability, and how they contribute to more readable and maintainable code.

Furthermore, practical examples will illustrate how vectorization can be applied to real-world problems, highlighting the performance gains and ease of implementation that JAX provides. By the end of this chapter, you'll be equipped with the knowledge to effectively utilize vectorization in your data science projects, maximizing the potential of JAX's capabilities.