What you'll learn
Be able to run deep learning models with Keras on Tensorflow 2 backend
Run Deep Neural Networks on a real-world scientific protein dataset
Understand how to feed own data to deep learning models (i.e. handling the notorious shape mismatch issue)
Understand Deep Learning, CNN, dropout, functional API with minimal of math
Understand and use Keras' functional API to create models with multiple inputs and outputs
Learn how to do Transfer Learning practically
Stunning SUPPORT. I answer questions on the same day.

Requirements
You should be able to use Python (if, while, lists. Everything else will be covered in the course)
NO prior knowledge of machine learning is assumed

Description
**UPDATED: Now using Tensorflow 2. Please post in Q&A if you have any trouble. I'm here to help**
**UPDATED 11-2021: Added a section on Practical Transfer Learning**
TensorFlow is by far, the most popular library for deep learning. Backed by Google, it is a solid investment of your time and efforts if you want to succeed in the area of machine learning and AI. The issue most people face is that getting started with Tensorflow guides usually delve too deeply into unnecessary mathematics.
That is where this course comes in. While some theory is important, a lot of it is just not needed when you're just getting started!
This course is for you
if you are new to Machine Learning
but want to
learn it without all the complicated math
. This course is also for you if you have had a machine learning course but could never figure out how to use it
to solve your own problems