Deep-Learning-Papers-Reading-Roadmap vs Real-Time-Voice-Cloning

Deep-Learning-Papers-Reading-Roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech! (by floodsung)

Deep Learning

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Real-Time-Voice-Cloning

Clone a voice in 5 seconds to generate arbitrary speech in real-time (by CorentinJ)

Deep Learning Pytorch Tensorflow Tts voice-cloning Python

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Deep-Learning-Papers-Reading-Roadmap		Real-Time-Voice-Cloning
	Project
5	Mentions	96
37,548	Stars	51,091
-	Growth	-
0.0	Activity	0.0
over 1 year ago	Latest Commit	23 days ago
Python	Language	Python
-	License	GNU General Public License v3.0 or later

The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Deep-Learning-Papers-Reading-Roadmap

Posts with mentions or reviews of Deep-Learning-Papers-Reading-Roadmap. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-09-08.

[D] Resources for Understanding The Original Transformer Paper
5 projects | /r/MachineLearning | 8 Sep 2021

https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap - This one is a bit dated so it doesn’t contain all of the papers that you need to read to get up to date but I think you should definitely read all of the papers in this list and implement as much as you can.
4 ML Roadmaps to Help You Find Useful Resources to Learn From
1 project | /r/learnmachinelearning | 11 Jul 2021

Deep Learning Papers Reading Roadmap
Should I implement every famous DL paper? [D]
1 project | /r/MachineLearning | 16 Jun 2021

I found a really great list of introductory and popular dl papers (github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap) and I would absolutely implement every paper on this list if I had the time (at least a mini version e.g. CIFAR10 instead of ImageNet). Is is essential for me to implement every single paper on that list to become a good DL researcher and to start reading/implementing more recent ones? All the papers on the list are from before 2017 and I can't wait to start exploring the latest research! Would I be able to get away with just implementing a handful of papers from that list?
[D] How did you implement papers with models that required a lot of GPUs to train?
1 project | /r/MachineLearning | 27 May 2021

I'm self-learning ML and trying to implement the papers listed here but I don't have access to hundreds of free GPUs like those corpos do.
Looking for Beginner CV Resources
1 project | /r/computervision | 7 Feb 2021

Definitely check out this list https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap It's all papers, you should get used to reading scientific material.

Real-Time-Voice-Cloning

Posts with mentions or reviews of Real-Time-Voice-Cloning. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-02-12.