Summary

This chapter provided a comprehensive guide to breaking into the Sec-ML industry. It contains all the tools, tricks, and tips that you need to become a data scientist or ML practitioner in the domain of cybersecurity. We began by looking at a set of resources that you can leverage to study ML – both conceptually and hands-on. We also provided several references to books that will help you with the hands-on implementation of ML models in security-related fields. We also shared a question bank that contains commonly asked theory questions in data science interviews, followed by some conceptual, case study-based questions. While neither the resources nor the interview questions are exhaustive, they provide a good starting point.

Finally, the skills and knowledge you have learned so far in this book are of no use if you do not apply them to boost your portfolio. To facilitate this, four project blueprints were presented, along with helpful hints on implementation. We...