Data Science | Machine Learning with Python for Researchers
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The Data Science and Python channel is for researchers and advanced programmers

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⚑️ LLMRec: Large Language Models with Graph Augmentation for Recommendation

πŸ–₯ Github: https://github.com/hkuds/llmrec

πŸ“• Paper: https://arxiv.org/abs/2311.00423v1

⏩ Project: https://llmrec.github.io/

🌐 Dataset: https://llmrec.github.io/#

https://t.iss.one/DataScienceT
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πŸ–₯ TORCH UNCERTAINTY

Comprehensive PyTorch Library for deep learning uncertainty quantification techniques.

pip install torch-uncertainty

πŸ–₯ Github: https://github.com/ensta-u2is/torch-uncertainty

πŸ“• Paper: https://arxiv.org/abs/2311.01434v1

⏩ Project: https://llmrec.github.io/

πŸ‘£ Api: https://torch-uncertainty.github.io/api.html

🌐 Dataset: https://paperswithcode.com/dataset/cifar-10

https://t.iss.one/DataScienceT
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PETA: Evaluating the Impact of Protein Transfer Learning with Sub-word Tokenization on Downstream Applications

πŸ–₯ Github: https://github.com/ginnm/proteinpretraining

πŸ“• Paper: https://arxiv.org/pdf/2310.17415v1.pdf

πŸ”₯ Datasets: https://paperswithcode.com/dataset/peta-protein

⭐ Tasks: https://paperswithcode.com/task/language-modelling

https://t.iss.one/DataScienceT
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🎧 Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model

Video2Music: Suitable Music Generation from Videos using an Affective Multimodal Transformer model.

πŸ–₯ Github: https://github.com/amaai-lab/video2music

πŸ“• Paper: https://arxiv.org/abs/2311.00968v1

⏩ Demo: https://llmrec.github.io/

🌐 Dataset: https://zenodo.org/records/10057093

https://t.iss.one/DataScienceT
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Top execs from billion-dollar giants are whispering about next crypto "GEM". Want in?

This Tuesday, Blockchain Whispers pulls back the curtain. Join the insiders now: https://t.iss.one/+c5yEZuGFtsc5NDlk
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πŸš€ Introducing YOLO-NAS Pose : A Game-Changer in Pose Estimation πŸš€

This Model is a redefinition of pose estimation's potential.

πŸ–₯ Github: https://github.com/Deci-AI/super-gradients

πŸ“• Notebook: https://colab.research.google.com/drive/1O4N5Vbzv0rfkT81LQidPktX8RtoS5A40

πŸš€ Demo: https://huggingface.co/spaces/Deci/YOLO-NAS-Pose-Demo

🌐 Colab: https://colab.research.google.com/drive/1agLj0aGx48C_rZPrTkeA18kuncack6lF

https://t.iss.one/DataScienceT
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Bilingual Corpus Mining and Multistage Fine-Tuning for Improving Machine Translation of Lecture Transcripts

πŸ–₯ Github: https://github.com/shyyhs/CourseraParallelCorpusMining

πŸ“• Paper: https://arxiv.org/abs/2311.03696v1

πŸ”₯ Datasets: https://paperswithcode.com/dataset/aspec

https://t.iss.one/DataScienceT
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Large Language Models (in 2023)

An excellent summary of the research progress and developments in LLMs.

Hyung Won chung, OpenAI (ex.Google and MIT Alumni) made this content publicly available. It's a great way to catch up on some important themes like scaling and optimizing LLMs.

Watch his talk here and Slides shared here.

https://t.iss.one/DataScienceT
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πŸš€ Whisper-V3 / Consistency Decoder

Improved decoding for stable diffusion vaes.

- Whisper paper: https://arxiv.org/abs/2212.04356
- Whisper-V3 checkpoint: https://github.com/openai/whisper/discussions/1762
- Consistency Models: https://arxiv.org/abs/2303.01469
- Consistency Decoder release: https://github.com/openai/consistencydecoder

https://t.iss.one/DataScienceT
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NVIDIA just made Pandas 150x faster with zero code changes.

All you have to do is:
%load_ext cudf.pandas
import pandas as pd


Their RAPIDS library will automatically know if you're running on GPU or CPU and speed up your processing.

You can try it in this colab notebook

GitHub repo: https://github.com/rapidsai/cudf

https://t.iss.one/DataScienceT
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πŸͺž Mirror: A Universal Framework for Various Information Extraction Tasks

πŸ–₯ Github: https://github.com/Spico197/Mirror

πŸ“• Paper: https://arxiv.org/abs/2311.05419v1

🌐 Dataset: https://paperswithcode.com/dataset/glue

https://t.iss.one/DataScienceT
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⚑️ LCM-LoRA: A Universal Stable-Diffusion Acceleration Module

Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference.

pip install diffusers transformers accelerate gradio==3.48.0

πŸ–₯ Github: https://github.com/luosiallen/latent-consistency-model

πŸ“• Paper: https://arxiv.org/abs/2311.05556v1

🌐 Project: https://latent-consistency-models.github.io

πŸ€— Demo: https://huggingface.co/spaces/SimianLuo/Latent_Consistency_Model

https://t.iss.one/DataScienceT
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πŸ”Š Qwen-Audio: Advancing Universal Audio Understanding via Unified Large-Scale Audio-Language Models

Π‘hat & pretrained large audio language model proposed by Alibaba Cloud.

🐱 Github: https://github.com/qwenlm/qwen-audio

πŸš€ Demo: https://qwen-audio.github.io/Qwen-Audio/

πŸ“• Paper: https://arxiv.org/abs/2311.07919v1

⏩ Dataset: https://paperswithcode.com/dataset/vocalsound

https://t.iss.one/DataScienceT
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