-
Book Overview & Buying
-
Table Of Contents
Applied Computational Thinking with Python - Second Edition
By :
This chapter provided a thorough introduction to ML with Python, covering the basics and progressing to practical applications. The key topics included defining ML, exploring its life cycle, and discussing different algorithms, including DL. Practical skills were emphasized, such as using Python packages such as Keras for data modeling, neural network definition, model training and evaluation, and making predictions. This chapter also touched on data classification and clustering. We will continue to explore some of the topics that were discussed here in the next chapter. We will also see some of these applications in the examples provided in Chapter 18, Advanced Applied Computational Thinking Problems.