اینجا کلی سرویس ابری رایگان هست که می‌تونید پروژه‌های آزمایشی خودتونو روشون پیاده کنید:
https://github.com/ripienaar/free-for-dev

#منابع

❇️ @AI_Python

مصاحبه‌ جذابی از گروه Fully connected با دکتر Vahid Behzadan و با موضوع امنیت سیستم‌های هوشمند انجام شده است. از طریق لینک زیر می‌تونید به ویدیو دسترسی داشته باشید.


https://youtu.be/8LGH9lfBDXw

#فیلم

❇️ @AI_Python

A Deep Learning Road Map And Where To Start

https://medium.com/@ArianAmani/the-deep-learning-road-map-that-i-took-c29120b0f5e2

Text-Free Learning of a Natural Language Interface for Pretrained Face Generators


pip install git+https://github.com/openai/CLIP.git

Github: https://github.com/duxiaodan/fast_text2stylegan

Paper: https://arxiv.org/abs/2209.03177v1

Dataset: https://paperswithcode.com/dataset/ffhq

100s 𝗼𝗳 𝗡𝗟𝗣 𝗣𝗮𝗽𝗲𝗿𝘀 𝘄𝗶𝘁𝗵 𝗖𝗼𝗱𝗲! 💡

I found this amazing website, it can help you keep track of recent advancements in NLP, by offering an updated list of the latest NLP research papers.

Also it provides a link to the Github repos, making it a valuable resource for ML researchers and practitioners. You can check the following link:
https://index.quantumstat.com/

#منابع #پردازش_زبان_طبیعی #مقاله #کتاب

❇️ @AI_Python

GNNs Learn To Smell & Awesome NeurReps

1) Back in 2019, Google AI started a project on learning representations of smells. From basic chemistry we know that aromaticity depends on the molecular structure, e.g., cyclic compounds. In fact, the whole group of ”aromatic hydrocarbons” was named aromatic because they actually has some smell (compared to many non-organic molecules). If we have a molecular structure, we can employ a GNN on top of it and learn some representations - that is a tl;dr of smell representation learning with GNNs.

Recently, Google AI released a new blogpost describing the next phase of the project - the Principal Odor Map that is able to group molecules in “odor clusters”. The authors conducted 3 cool experiments: classifying 400 new molecules never smelled before and comparison to the averaged rating of a group of human panelists; linking odor quality to fundamental biology; and probing aromatic molecules on their mosquito repelling qualities. The GNN-based model shows very good results - now we can finally claim that GNNs can smell! Looking forward for GNNs transforming the perfume industry 📈

2) The NeurReps commnuity (Symmetry and Geometry in Neural Representations) is curating the Awesome List of resources and research related to the geometry of representations in the brain, deep networks, and beyond. A great resource for Neuroscience and Geometric DL folks to learn about the adjacent field!

میدونستید گوگلی ها برای یافتن بهترین دسر غذاشون یه تحقیقاتی انجام دادن و مقاله هم کردن و تو nips چاپ کردن؟
@ai_python

StoryDALL-E: Adapting Pretrained Text-to-Image Transformers for Story Continuation

Github

Paper

Model

Demo

Dataset

#مقاله

❇️ @AI_Python

Machine Learning on Geographical Data

#Geodata #ML #MachineLearning #Python
#AI #DataScience #artificialIntelligence

https://reconshell.com/machine-learning-on-geographical-data/

Entity Tagging: Extracting Entities in Text Without Mention Supervision

Github: https://github.com/facebookresearch/groov

Paper: https://arxiv.org/abs/2209.06148v1

Model: https://github.com/adymaharana/storydalle/blob/main/MODEL_CARD.MD

Dataset: http://manikvarma.org/downloads/XC/XMLRepository.html

🤖 DAMO ConvAI

The official repository which contains the codebase for Alibaba DAMO Conversational AI.

⚙️ Github
➡️ Paper
📎 Tasks
🗒 Text-to-SQL Parsing

#مقاله

❇️ @AI_Python

CLIP-ViP: Adapting Pre-trained Image-Text Model to Video-Language Representation Alignment

Github

Paper

Dataset

#مقاله

❇️ @AI_Python

دوره رایگان از محققان شرکت DeepMind و Qualcomm و دانشگاه MIT برگزار میگردد.

Learn category theory foundations from the lens of ML, grounded in concrete papers. Open to all!

Sign up: https://cats.for.ai

#منابع

❇️ @AI_Python

مهندسین داده

Robust Online Allocation with Dual Mirror Descent


http://ai.googleblog.com/2022/09/robust-online-allocation-with-dual.html

📚 Weekend Reading

This week brought quite a few interesting papers and resources - we encourage you to invest there some time:

Geometric multimodal representation learning by Yasha Ektefaie, George Dasoulas, Ayush Noori, Maha Farhat, and Marinka Zitnik. A survey of 100+ papers on graphs combined with other modalities and a framework of multi-modal approaches for natural sciences like physical interaction, molecular reasoning, and protein modeling.

Clifford Neural Layers for PDE Modeling by Johannes Brandstetter, Rianne van den Berg, Max Welling, Jayesh K. Gupta. If you thought you know all the basics from the Geometric Deep Learning Course - here is something more challenging. The authors introduce the ideas from Geometric Algebra into ML tasks, namely, Clifford Algebras that unify numbers, vectors, complex numbers, quaternions, and have additional primitives to incorporate plane and volume segments. The paper gives a great primer on the math and applications. You can also watch a very visual YouTube lecture on Geometric Algebras.

Categories for AI (Cats4AI) - an upcoming open course on Category Theory created by Andrew Dudzik, Bruno Gavranović, João Guilherme Araújo, Petar Veličković, and Pim de Haan. “This course is aimed towards machine learning researchers, but approachable to anyone with a basic understanding of linear algebra and differential calculus. The material is self-contained and all the necessary background will be introduced along the way.” Don’t forget your veggies

#منابع

❇️ @AI_Python

Google at Interspeech 2022


http://ai.googleblog.com/2022/09/google-at-interspeech-2022.html

Real-time Online Video Detection with Temporal Smoothing Transformers

git clone --recursive git@github.com:zhaoyue-zephyrus/TeSTra.git

⚙️ Github
🗒 Paper
🦾 Dataset

#مقاله

افزونه گوگل کروم، برای فعال نگه داشتن سشن colab

https://chrome.google.com/webstore/detail/colab-alive/eookkckfbbgnhdgcbfbicoahejkdoele?hl=en-GB

Text2Light: Zero-Shot Text-Driven HDR Panorama Generation

Text2Light can generate HDR panoramas in 4K+ resolution using free-form texts solely.

conda env create -f environment.yml
conda activate text2light

⚙️ Github
💡 Project
💻 Model
🗒 Paper
🦾 Tutorial

#مقاله