Welcome to my GitHub profile ! The objective of my projects is to make Deep Learning more accessible, and provide real-world examples to enhance education and research in the field ! 😋

The goal is to aggregate a wide range of Deep Learning topics in one place with a common abstraction, making it easier for you to dive into this fascinating field. Each repository not only focuses on a specific area of Deep Learning, but also includes links to tutorials and reference papers. These resources are carefully selected to help you grasp both the practical and theoretical aspects of Deep Learning, which can sometimes be challenging to find.

Currently developped topics :

• Image classification *
• Object detection
• Siamese networks
• Speech-To-Text (STT)
• Text-To-Speech (TTS)
• Generative Adversarial Networks (GAN)
• Object segmentation
• Natural Language Processing (NLP) : Masked Language Modeling (MLM)
• Natural Language Processing (NLP) : Question-Answering (Q&A)
• Natural Language Processing (NLP) : Text Generation
• Natural Language Processing (NLP) : Translation
• Optical Character Recognition (OCR)
• Reinforcment Learning (RL) for single-player games
• Reinforcment Learning (RL) for adversarial games

Additional utilities :

• Custom losses / metrics / callbacks
• Dataset processing / analyzing
• Plot / visualization utils
• Audio processing
• Image processing
• Text processing
• Multi-threading framework

Practical use cases :

• Speaker Verification (SV)
• Face Recognition : the code is available but the model is not performant enough yet
• Search text in audios / videos
• Live transcription / subtitle generation : some models tend to be accurate enough for transcription but they will be further improved
• Text-To-Speech logger : logging-based logger that reads your logs with TTS models
• Optical Character Recognition (OCR) : this projects allows to detect text in an image, and performs OCR on the detected text

All topics are released in separate repositories to make it easier to learn / experiments with dedicated codes and ressources.

* It is a demonstration code to show how to subclass BaseModel. I will add a dedicated repository later for general classification (text / image / ...).

Contacts :

• Mail : [email protected]
• Discord : yui0732

The goal of these projects is to support and advance education and research in Deep Learning technology. To facilitate this, all associated code is made available under the GNU Affero General Public License (AGPL) v3, supplemented by a clause that prohibits commercial use (cf the LICENCE file).

These projects are released as "free software", allowing you to freely use, modify, deploy, and share the software, provided you adhere to the terms of the license. While the software is freely available, it is not public domain and retains copyright protection. The license conditions are designed to ensure that every user can utilize and modify any version of the code for their own educational and research projects.

If you wish to use this project in a proprietary commercial endeavor, you must obtain a separate license. For further details on this process, please contact me directly.

For my protection, it is important to note that all projects are available on an "As Is" basis, without any warranties or conditions of any kind, either explicit or implied. However, do not hesitate to report issues on the repository's project, or make a Pull Request to solve it 😄

If you find this project useful in your work, please add this citation to give it more visibility ! 😋

@misc{yui-mhcp
    author  = {yui},
    title   = {A Deep Learning projects centralization},
    year    = {2021},
    publisher   = {GitHub},
    howpublished    = {\url{https://github.com/yui-mhcp}}
}

Thanks to @Ananas120 for his contribution and sharing his implementation of Transformers architectures + his master thesis' code about Q&A !