Practical Deep Learning with Tensorflow 2 and Keras

This course is for you if you are new to Machine Learning but want to learn it without all the 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. 

In this course, we will start from very scratch. This is a very applied course, so we will immediately start coding even without installation! You will see a brief bit of essential theory and then we will get into the environment setup and explain almost all concepts through code. You will be using Keras and Tensorflow 2 one of the easiest and most powerful machine-learning tools out there. 

You will start with a basic model of how machines learn and then move on to higher models such as: 

• Convolutional Neural Networks 

• Residual Connections 

• Inception Module

All with only a few lines of code. All the examples used in the course come with a starter code which will get you started and remove the grunt effort. The course also includes finished codes for the examples run in the videos so that you can see the end product should you ever get stuck.  

Target Audience: 

• Anyone who wants to learn machine learning (this course is a soft introduction).

• Anyone who knows machine learning and wants to learn deep learning (this course focuses on deep learning).

• Anyone who knows deep learning but needs help applying their knowledge in practice (this is a very applied course). 

• Anyone who is comfortable with deep learning models but has trouble processing examples beyond the toy examples covered in typical courses (this course has a real-world case study and not just toy examples).

• Anyone who Is a researcher or educator working in machine learning and wants to move from theory to practice.

What you need to know:

• Python basics (installation, if, loops, lists) - Everything else will be covered in the course.

• No machine learning background is assumed (but we keep the theory to a minimum).