Practical Deep Learning with Tensorflow 2.x and Keras

Practical Deep Learning with Tensorflow 2.x and Keras

**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.

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 absolutely 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.x -- 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

• Functional API of Keras / Tensorflow 2.x

• Transfer Learning

In this course, we explain concepts using not only toy datasets but also a real-world dataset from the bioinformatics domain. While you may not be interested in this particular domain, you would still learn a lot of important concepts that are involved in taking data from the real world and feeding it to ML models. This is the aspect of ML that is missing from almost all courses available on the internet today! Doing this would mean that you would be able to solve problems of your own industry after finishing this course.

All with only a few lines of code. All the examples used in the course come with a starter code that 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.  Do checkout the preview lectures on this page to get a better feel of the teaching style used in this course and how it can help you learn quickly.

I provide unmatched support. All questions are answered within 24 hours. Try me and see ...  =]

Learn to apply Tensorflow to YOUR problems. Follow a complete pipeline including pre-processing and training for ML.

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What you will 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)

Rating: 4.45

Level: Beginner Level

Duration: 4 hours

Instructor: Dr. Mohammad Nauman