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Code Repository for Python Deep Learning for Beginners, published by Packt

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Python Deep Learning for Beginners [Video]

This is the code repository for Python Deep Learning for Beginners [Video], published by Packt. It contains all the supporting project files necessary to work through the video course from start to finish.

About the Video Course

This course will teach you to apply deep learning concepts using Python to solve challenging tasks. You will build a Python deep learning-based image recognition system and learn to deploy and integrate images into web apps or phone apps.

What You Will Learn

  • The history of neural networks, and where they are now
  • Get a brief understanding of trade-offs and practical implementation aspects
  • Get hands-on experience building basic neural network models (no math!) using Python
  • Ramp up productivity in model building by leveraging popular frameworks
  • Implement some state-of-the-art computer vision algorithms using deep learning and Python
  • Build and learn to deploy a practical deep learning application with Python
  • Get an overview of current skills, frameworks, tools, and techniques for the AI market
  • Build a deep learning-based image recognition system using Python and learn how to deploy and integrate it into web apps or phone apps

Instructions and Navigation

Assumed Knowledge

To fully benefit from the coverage included in this course, you will need:
This course targets people who want to get started with the basics of deep learning but find themselves confused by the complex math equations and the esoteric programming paradigms currently out there for deep-learning. Some experience of Python is recommended, but not essential.

Technical Requirements

This course has the following software requirements:
SETUP AND INSTALLATION Minimum Hardware Requirements For successful completion of this course, students will require the computer systems with at least the following:

OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit

Processor: Intel Core i5 or equivalent

Memory: 8 GB RAM

Storage: 35 GB available space

Recommended Hardware Requirements For an optimal experience with hands-on labs and other practical activities, we recommend the following configuration:

OS: Windows 7 SP1 64-bit, Windows 8.1 64-bit or Windows 10 64-bit

Processor: Intel Core i7 or equivalent

Memory: 48 GB RAM

Storage: 35 GB available space

Software Requirements

OS: Windows 7 or Windows 10

Browser: Google Chrome, Latest Version

Code Editor: Atom IDE, Latest Version

Others: Python3 installed using the Anaconda package or equivalent, Tensorflow r1.4

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