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File Name: The Multilayer Artificial Neural Network Course with Python

Content Source: https://www.udemy.com/course/hoangquyla-the-multilayer-artificial-neural-network-course-with-python/

Genre / Category: Programming

File Size : 3.5GB

Publisher: udemy



Requirements


  • Decent Python competencies are required
  • Description


Interested in the discipline of Deep learning? Then this direction is for you!


This path has been designed to share my understanding and assist you research complicated theory, algorithms, and coding libraries in a easy way.


I will stroll you step by using step into the world of synthetic neural networks.


This direction is exciting and exciting, however at the equal time, we dive deep into the synthetic neural network. It is structured the following way:


Section 1: Introduction.

Section 2: Fundamental Neural Network

Section 3: Modelling neural networks

Section 4: Classifying Handwritten digits

There are a lot of equipment that we will cowl in this course. These equipment consist of TensorFlow, back-propagation, feed-forward network, and so on. A lot of different on-line publications did no longer cowl back-propagation and this is a large MISTAKE as back-propagation is an necessary topic. This direction will now not solely cowl back-propagation in principle however additionally put into effect it in the project. So you will have a deep grasp of back-propagation. You can empress your practicable organisation with the aid of displaying the venture with back-propagation.


Moreover, the route is packed with sensible workout routines that are based totally on real-life examples. So now not solely will you study the theory, however you will additionally get some hands-on exercise constructing your very own models. There are three massive tasks and some small tasks to exercise what you have discovered in the course of the course. These tasks are listed below:


  • Handwritten Digit.
  • Birth weights
  • MNIST

Become an synthetic neural community guru today! I will see you internal the course!


Who this route is for:

  • Anyone involved in Deep Learning
  • Students who have at least excessive faculty understanding in math and who choose to begin mastering Deep Learning
  • Any college students in university who favor to begin a profession in Data Science
  • Any records analysts who choose to stage up in Deep Learning