Requirements for Hands-On Approach to Deep Learning

This a bridging chapter in which we introduce some of the concepts needed to start building deep learning models in Python. The chapter starts with basic principles related to data manipulation and ends with explanation on how to set up the modelling environment. Some high level programming concepts which are very easy to acquire within a short space of time are presented in order to give the reader a picture of what to expect in examples that will be presented in the book. An explanation of vectors and matrices in the context of deep learning is provided. Furthermore, the concept of tensors as a subset of multi-dimensional arrays is touched. Like any other programming language, Python has a unique way of accessing and manipulating these arrays which are also explained in this chapter. As the key component of hands-on approach, we also include here a discussion on some environments supported for deep learning model evaluation, both offline and online. Finally, some self-evaluation exercises are given to emphasize the key takeaways from the chapter. We also provide a list of references for further reading.