Practical Deep Learning with Tensorflow 2 and Keras

person icon Mohammad Nauman

Practical Deep Learning with Tensorflow 2 and Keras

Apply machine learning by following a complete pipeline!

updated on icon Updated on Sep, 2023

language icon Language - English

person icon Mohammad Nauman

architecture icon Data Science,Deep Learning

Lectures -30

Resources -2

Duration -3.5 hours


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Course Description

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 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 -- 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 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)  

  • Knows machine learning and wants to learn deep learning (this course focuses on deep learning) 

  • Knows deep learning but needs help applying their knowledge in practice (this is a very applied course) 

  • 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) 

  • 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)


What will you learn in this course:

  • Basics of machine learning with minimal math
  • Applying machine learning principles to solve a real-world case study
  • Understand the often problematic shape issue
  • Use Keras's functional API
  • Learn how to use Google's GPUs to speed up your experiments for free
  • Tips on avoiding mistakes


What are the prerequisites for this course?

  • Basic Programming Knowledge
  • Basic Python Knowhow
  • No ML background assumed (but will help if you have seen some of it before)
Practical Deep Learning with Tensorflow 2 and Keras


Check out the detailed breakdown of what’s inside the course

3 Lectures
  • play icon About the Instructor 01:37 01:37
  • play icon Dive into Machine Learning 13:10 13:10
  • play icon Making Predictions 07:02 07:02
A Bit of Theory
4 Lectures
Installation and Setup
2 Lectures
Say Hi to Keras
4 Lectures
Real World Case Study: Predicting Protein Functions
7 Lectures
Convolutional Neural Networks (CNN)
4 Lectures
Graph-based Models
3 Lectures
Finishing Touches
2 Lectures

Instructor Details

Mohammad Nauman

Mohammad Nauman

PhD, programmer, researcher, designer and teacher.

I have a PhD in Computer Sciences and a PostDoc from the Max Planck Institute for Software Systems. I have been programming since early 2000 and have worked with many different languages, tools and platforms. I have an extensive research experience with many state-of-the-art models to my name. My research in Android security has led to some major shifts in the Android permission model.

I love teaching and the most important reason I upload on Tutorialspoint is to make sure people can find my content. If you have any problem with finances and you want to take my courses, please visit my site (link on the left). I am more than willing to give out coupons that will make the course more affordable for you.  

You can see all the different areas I've worked with on my site as well as on my github page.

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