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Getting Started with Deep Science
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tuhinm@...
Following specialization is a very good starting point for Deep learning. Andrew Ng is one of the best in teaching ML/DL in Mooc courses.
https://www.coursera.org/specializations/deep-learning |
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denys.marushchak@...
Great start is a Stanford course by Fei-Fei Li, et. al.: "Convolutional Neural Networks for Visual recognition"
http://cs231n.stanford.edu/ Very rich materials including syllabus and video lectures are posted for free online. Of course you need to have basics of Python to start coding. |
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denys.marushchak@...
A great start is a Stanford course CS231n by Fei-Fei Li, et. al.: "Convolutional Neural Networks for Visual Recognition"
http://cs231n.stanford.edu/ It has very rich materials available for free online: notes, syllabus and of course video lectures. If you are impatient and interested in image recognition, directly jump into Module 2: Convolutional Neural Networks. Prerequisite would be a basic knowledge of Python. |
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malineni maurya
1)Andrew Ng's coursera deeplearning specialisation takes bottom-up approach which means he explains things from scratch and builds things on the base concepts introduced. 2)Jeremy Howard's fast.ai course does things from the top down. So you get into action first and learn things later. This is more suitable if you come from a programming background 3)Siraj Raval has his own way of explaining complex things in an engaging way. You can check out his videos on youtube -- Regards, Maurya |
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The initial project of LF Deep Learning is the Acumos AI Project (https://www.acumos.org/), a comprehensive platform for AI model discovery, development and sharing.
The below two links seem to be good to get started with: 1. Welcome to Acumos Documentation! 2. Acumos Wiki
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Welcome to Acumos Documentation! Acumos Wiki Cheers, Donald
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ashi.mahe@...
Am deep learning/Science enthusiast.
What is the better way to get stated? |
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