Part 1 – Building a Minimum Viable Product

AI projects begin with planning and understanding the difficulty of the given problem. Once the scope of the project is clearly defined, the next step is to create a Minimum Viable Product (MVP). For a project based on deep learning, this process involves preparing a set of data and exploring various model architectures to come up with a working solution to the problem. In this first part of the book, we explain how you can carry out the aforementioned steps efficiently by exploiting the various resources available.

This part comprises the following chapters:

• Chapter 1, Effective Planning of Deep Learning-Driven Projects
• Chapter 2, Data Preparation for Deep Learning Projects
• Chapter 3, Developing a Powerful Deep Learning Model
• Chapter 4, Experiment Tracking, Model Management, and Dataset Versioning