applied-ml
đź“š Papers & tech blogs by companies sharing their work on data science & machine learning in production. (by eugeneyan)
DeepFaceLab
DeepFaceLab is the leading software for creating deepfakes. (by iperov)
| applied-ml | DeepFaceLab | |
|---|---|---|
| 13 | 91 | |
| 25,984 | 43,236 | |
| - | - | |
| 3.0 | 4.4 | |
| 5 days ago | 6 months ago | |
| Python | ||
| MIT License | GNU General Public License v3.0 only |
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.
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.
applied-ml
Posts with mentions or reviews of applied-ml.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-12.
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[D] Favorite ML Youtube Channels/Blogs/Newsletters
Also, have any of you stumbled across any cool GitHub repos like this one: https://github.com/eugeneyan/applied-ml ?
- Curated Papers on Machine Learning in Production
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Top Github repo trends in 2021
The second repo I LOVE is Eugene Yan’s Applied ML repository. This is a brilliant idea to create and actually something I was planning on sort of casually doing in my non-existent free time… Anyhow, it is a curated list of technical posts from top engineering teams (Netflix, Amazon, Pinterest, Linkedin, etc.) detailing how they built out different types of AI/ML systems (e.g. forecasting, recommenders, search and ranking, etc.). Ofc, it focuses on AI/ML, but something similar could be made for the traditional or BI-oriented analytics stack, as well as the streaming world, super high value for practitioners! Btw-one of my favorite things at BCG used to be looking at our IT architecture team’s reference architecture diagrams… the best way to understand technologies is to look at how a ton of stuff is architected… and its fun!
- Curated papers, articles, & blogs on data science and ML in production
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Messed up my career by pivoting to DS. Wondering if it's too late to switch to MLE
Applied ML: A collection of papers, articles, and blogs on ML in production by different companies (Netflix, Uber, Facebook, LinkedIn, etc)
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[D] A dilemma of an ML guy in industry
Eugene Yan's applied-ml has tons of case studies.
- Papers & tech blogs by companies sharing their work on data science & machine learning in production.
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My information dump for people trying to break into data science/interview notes
https://github.com/eugeneyan/applied-ml You may find some of his links interesting. I would avoid anything that refers to scaling up a platform as these are more backend engr focus. The more relevant posts to you are probably on the scale of blog posts that are product oriented like the ones I listed in section 4 (e.g. we wanted to solve X for our users and this is how we scoped and defined it). The technical aspects should come backseat to the business aspects. There's def a lot of companies/blog posts that he missed, but the internet is huge.
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[D] Can anyone point me to resources/case studies of companies/business creating infrastructure for their data needs?
Check the resources mentioned in applied-ml. It includes blog posts/papers from many companies describing how they built some ML product X.
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What content would be useful to intermediate Data Scientist
Check out this repo. They collect hundreds of case studies, broken down by dozens of methodologies from large real-world companies such as AirBnB, Nvidia, Uber, Netflix etc.
DeepFaceLab
Posts with mentions or reviews of DeepFaceLab.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-30.
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DeepFaceLab VS facefusion - a user suggested alternative
2 projects | 30 Jan 2024
- Civitai founder champions open source, downplays AI deepfake porn (article on venturebeat)
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roop-unleashed
AFAIK the only app which supports whole head swapping is DeepfaceLab but it needs to be trained with lots of images and lacks a proper GUI.
- Greta Thunberg apoyando a los "ambientalistas" jujeños.
- Silvio Santos apresentando o Jornal Nacional
- Free deepfake software? (No paywalls)
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What are the best AI tools for deepfakes?
I think DeepFaceLab is still the leading open source option.
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List of AI-Models
Click to Learn more...
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Chinese tech giant offering Deepfakes as a Service (DFaaS) for $145 - The service only needs three minutes of live-action video and 100 spoken sentences to generate a high-definition digital human.
Here it is for free: https://github.com/iperov/DeepFaceLab I guess the repo isn't available in China.
- Bourne movie montage but want to edit my friends picture over Matt Damon face.
What are some alternatives?
When comparing applied-ml and DeepFaceLab you can also consider the following projects:
awesome-mlops - A curated list of references for MLOps
faceswap - Deepfakes Software For All
awesome-ml-blogs - Curated list of technical blogs on machine learning · AI/ML/DL/CV/NLP/MLOps
DeepFaceLive - Real-time face swap for PC streaming or video calls
machine-learning-roadmap - A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
avatarify - Avatars for Zoom, Skype and other video-conferencing apps.
Cookbook - The Data Engineering Cookbook
Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time
ml-surveys - đź“‹ Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
Deep-Fakes
pipebase - data integration framework
fast-stable-diffusion - fast-stable-diffusion + DreamBooth
applied-ml vs awesome-mlops
DeepFaceLab vs faceswap
applied-ml vs awesome-ml-blogs
DeepFaceLab vs DeepFaceLive
applied-ml vs machine-learning-roadmap
DeepFaceLab vs avatarify
applied-ml vs Cookbook
DeepFaceLab vs Real-Time-Voice-Cloning
applied-ml vs ml-surveys
DeepFaceLab vs Deep-Fakes
applied-ml vs pipebase
DeepFaceLab vs fast-stable-diffusion