• views: 143
• date: 1 May 2025
• posted by: AD-TEAM

Implementing and training deep learning models in a free, integrated environment

What you'll learn
This course covers the general workflow of a deep learning project, implemented using PyTorch in Google Colab. At the end of the course, students will be proficient at using Google Colab as well as PyTorch in their own projects. Students will also learn about the theoretical foundations for various deep learning models and techniques, as well as how to implement them using PyTorch. Finally, the course ends by offering an overview on general deep learning and how to think about problems in the field; students will gain a high-level understanding of the role deep learning plays in the field of AI.
Learn how to utilize Google Colab as an online computing platform in deep learning projects, including running Python code, using a free GPU, and working with external files and folders
Understand the general workflow of a deep learning project
Examine the various APIs (datasets, modeling, training) PyTorch offers to facilitate deep learning
Learn about the theoretical basis for various deep learning models such as convolutional networks or residual networks and what problems they address
Gain an overview understanding of deep learning in the context of the artificial intelligence field and its best practices
Requirements
Familiarity with Python programming (including classes, functions, context managers)
Basic linear algebra and calculus (briefly used during the discussions on various deep learning models and techniques)
Description
This course covers the general workflow of a deep learning project, implemented using PyTorch in Google Colab. At the end of the course, students will be proficient at using Google Colab as well as PyTorch in their own projects. Students will also learn about the theoretical foundations for various deep learning models and techniques, as well as how to implement them using PyTorch. Finally, the course ends by offering an overview on general deep learning and how to think about problems in the field; students will gain a high-level understanding of the role deep learning plays in the field of AI.
Learn how to utilize Google Colab as an online computing platform in deep learning projects, including running Python code, using a free GPU, and working with external files and folders
Understand the general workflow of a deep learning project
Examine the various APIs (datasets, modeling, training) PyTorch offers to facilitate deep learning
Learn about the theoretical basis for various deep learning models such as convolutional networks or residual networks and what problems they address
Gain an overview understanding of deep learning in the context of the artificial intelligence field and its best practices
Who this course is for:
AI enthusiasts interested in getting started on deep learning
Programmers familiar with deep learning looking to gain a comprehensive understanding of various deep learning models and techniques

More Info




   
   
   

Forex Trading

Crypto Trading. 20 USD Bonus after KYC

We need your support!
Make a donation to help us stay online
        
Bitcoin (BTC)
bc1q08g9d22cxkawsjlf8etuek2pc9n2a3hs4cdrld
	
Bitcoin Cash (BCH)
qqvwexzhvgauxq2apgc4j0ewvcak6hh6lsnzmvtkem

Ethereum (ETH)
0xb55513D2c91A6e3c497621644ec99e206CDaf239

Litecoin (LTC)
ltc1qt6g2trfv9tjs4qj68sqc4uf0ukvc9jpnsyt59u

USDT (ERC20)
0xb55513D2c91A6e3c497621644ec99e206CDaf239

USDT (TRC20)
TYdPNrz7v1P9riWBWZ317oBgJueheGjATm

0 1 2 3 4 5

| Print version |

	Information
		Users of GUESTS are not allowed to comment this publication.