two target audiences


A. Data Scientists & Deep/Machine Learning researchers.

Are you worried about an upcoming interview? Perhaps you’re getting interviews but no offers? Want to be fully confident when answering the toughest AI interview questions?

If you are looking to pursue a career in the booming field of Artificial Intelligence (AI), this book is designed for you. Using this book a you can sharpen your applied mathematics for artificial intelligence and focus your learning curve on understanding the heart of deep learning algorithms.

This book will help first-time job seekers make the shift from the academia to employment. We recognise the data science job market has changed beyond recognition and finding that first position is more competitive than ever.

Recent graduates who are interested in pursuing a career in this field and need an in-depth knowledge of all aspects of artificial intelligence will find this book extremely valuable.

deep learning interviews book amazon
deep learning job interview questions  book amazon

B. Financial Engineers /Quants.

While many financial engineering books are available, the data science aspects behind the implementation of the models used in the field are mostly missing. The book is an invaluable piece that deserves a prominent spot on the shelf of every Quantitative Researcher looking to pursue a booming career in Deep Learning.

It is aimed at exploring many of the question types Quants are likely to encounter when undergoing job interviews in the field of Deep Learning. The available quant job roles are becoming tougher and tougher; thus, requiring all financial data scientists and engineers to be at their best whenever they face an interview panel.

All aspects covered to develop your readiness for the interview and the book is suitable for beginners and experienced financial engineers alike. Written from scratch, the book includes exclusive problems not found anywhere else.

The first four Chapters lay down the mathematical elements that will help you with both deep learning in general and, perhaps more importantly, the proper data science mindset.