Udemy - A deep understanding of deep learning (with Python intro) 2021
deep understanding

Udemy – A deep understanding of deep learning (with Python intro) 2021


A deep understanding of deep learning (with Python intro), is a deep learning course in PyTorch using a scientific and practical method with many examples and practice problems. By taking this course, you will gain a flexible, principled, and lasting experience in deep learning. You will learn the basic concepts with the help of this course and you will be able to easily learn new topics and trends in the future.

Note that this course is not just a summary of in-depth learning, but instead comprehensively examines why and how in-depth learning works and the many important concepts involved.

What you will learn in A deep understanding of deep learning (with Python intro):

  • Theory and mathematics behind deep learning
  • Build an artificial neural network
  • Feedforward and convolutional network architecture
  • Construction of models in the base of Torch
  • Differential and gradient descent coding
  • Scaling deep network models
  • Learn Python from scratch (without any coding experience)
  • How and why autoencoders work
  • Use transfer learning
  • Improve the performance of models using regularization
  • Weight optimization
  • Understand image convolution using pre-trained kernels
  • Use GPU for deep learning

Course specifications

Publisher: Udemy
Instructors: Mike X Cohen
Language: English
Level: Introductory
Number of Courses: 255
Duration: 54 hours and 25 minutes

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Udemy – AZ-104 Microsoft Azure Administrator Exam Certification 2021 2021-2

JavaScript Simplified – Advanced Course 2021-4 + Bonus Projects

Course topics:


deep understanding

Prerequisites for A deep understanding of deep learning (with Python intro):

Interest in learning about deep learning!
Python / Pytorch skills are taught in the course
A Google account (google-collab is used as the Python IDE)



deep understanding

Installation guide

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English subtitle

Quality: 720p

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Download section 1 – 4 GB
Download Section 2 – 4 GB
Download Section 3 – 4 GB
Download section 4 – 4 GB
Download section 5 – 4 GB
Download section 6 – 498 MB
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