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Practical Deep Learning with Tensorflow 2 and Keras

person icon Mohammad Nauman

4.4

Practical Deep Learning with Tensorflow 2 and Keras

Apply machine learning by following a complete pipeline!

updated on icon Updated on Jun, 2024

language icon Language - English

person icon Mohammad Nauman

English [CC]

category icon Data Science,Deep Learning

Lectures -30

Resources -2

Duration -3.5 hours

4.4

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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)

Goals

  • 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

Prerequisites

  • 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

Curriculum

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

Introduction
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
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Installation and Setup
2 Lectures
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Say Hi to Keras
4 Lectures
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Real World Case Study: Predicting Protein Functions
7 Lectures
Tutorialspoint
Convolutional Neural Networks (CNN)
4 Lectures
Tutorialspoint
Graph-based Models
3 Lectures
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Finishing Touches
2 Lectures
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Instructor Details

Mohammad Nauman

Mohammad Nauman


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