Applications of Machine Learning: Signal Processing

This chapter discusses some applications of machine learning in signal processing. The chapter starts by introducing signals and signal processing and its importance. Then, it sheds light on image classification and briefly discusses its workflow, applications, challenges, and Python coding implementation. Next, the chapter delves into the concept of neural style transfer, with its applications and implementation. The next section discusses the concept and implementation of feature extraction and dimensionality reduction. Next, anomaly detection is introduced with its different algorithms, applications, challenges, and implementation. Thereafter, adversarial input attacks and malicious input detection are discussed. Finally, natural language processing is introduced with its workflow, applications, challenges, and implementation. By the end of this chapter, the readers will have a lot of exposure to machine learning applications in signal processing and be able to use them in real life.