Welcome to Engineering Learning Machines!
This is the beginning of an exciting new journey into applying machine learning methods to practical problems. We will be starting by covering the fundamentals of recent deep learning models into much detail as to gain complete understanding of how they work, as well as their strengths and weaknesses. Moreover, we will be adding some concrete demonstrations of these models for practical applications, including how to collect the data, how set up the infrastructure, how to implement and deploy the model, and so on.
From an engineering perspective our aim is also to design robust code that can be used for production, therefore some software development expertise will be required. We are not leaving you with some messy Jupyter notebook, but we will look into how build a real ML-based product, a challenging proposition!
Stay tuned for the first wave of content that will cover the basic principles of neural networks used in deep learning.