Have you ever wondered why Deep Learning is taking over the world? Why it has revolutionized so many fields in research and industry? In this course, you will get answers to these questions through a real world use case. This course aims to achieve the best of both worlds: it will show you why machine learning and deep learning is powerful but will not focus on theory. It will show you how you can take your own problems and solve them using the state-of-the-art tool Keras, which is based on Python. It is the core tool used by the industry and academia for Machine Learning since it sits on top of great architectures such as tensorflow.
In this course, we will focus on practicals and deal with issues that newcomers to this field face. I will share all the headaches I had when I was learning this tool and show you how you can avoid them. I will start with an explanation of the very basics and get you quickly up to speed with the state-of-the-art models in a practical way. Most of this course is practical, code-based with real demonstrations. There is very little theory and that only when absolutely necessary.
What will I learn?
- An understanding of machine learning and deep learning from a practical viewpoint
- Solve a real world use case with me. This comes from a problem I solved for the Bioinformatics field which has immense potential to change the way the field works. (Recently, Google did something similar as well.) I will take you through the whole pipeline so that you can see how you can also solve problems that you are interested in.
- I will share all the problems that I faced as a newcomer so that you can save your time by avoiding them
- We will cover the basic models of Keras as well as the advanced models that few people have an understanding of
About the instructor:
- Teacher and researcher by profession
- PhD in Security and a PostDoc from Max Planck Institute for Software Systems, Germany
- 17+ years of working with computers and 15+ years of teaching experience
- 3+ years of working extensively with deep learning. I worked with almost all the modern tools as soon as they were released
What you need to know:
- Have a basic understanding of Python. (Keras understanding is not assumes. We will cover this in the course.)
- No ML or Deep Learning background assumed.
