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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Get started in Data Science with Microsoft's FREE course for beginners.

- 10 weeks
- 20 lessons
- Lecture notes
- 100% FREE

https://microsoft.github.io/Data-Science-For-Beginners/

https://t.iss.one/DataScienceT
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Fine-tuning MMS Adapter Models for Multi-Lingual ASR

MMS' Adapter training is both more memory efficient, more robust and yields better performance for low-resource languages.

πŸ€— Post: https://huggingface.co/blog/mms_adapters

πŸ–₯ Colab: https://colab.research.google.com/github/patrickvonplaten/notebooks/blob/master/Fine_Tune_MMS_on_Common_Voice.ipynb

πŸ–₯ Github: https://github.com/facebookresearch/fairseq/tree/main/examples/mms/asr

⭐️ Demo: https://huggingface.co/spaces/facebook/MMS

πŸ“• Paper: https://huggingface.co/papers/2305.13516

https://t.iss.one/DataScienceT
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⭐️ Text-Guided Adversarial Makeup 🫣

Novel facial privacy protection via adversarial latent codes. Makeup vs Face Recognition.

🌐 Review: https://t.ly/pBCP

🌐 Paper: arxiv.org/pdf/2306.10008.pdf

πŸ”₯ Code: github.com/fahadshamshad/Clip2Protect

https://t.iss.one/DataScienceT
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πŸš€ Fast Segment Anything

Fast Segment Anything Model reaches comparable performance with the SAM method at 50 times higher run-time speed.

git clone https://github.com/CASIA-IVA-Lab/FastSAM.git

πŸ–₯ Github: https://github.com/casia-iva-lab/fastsam

⭐️ Demo:https://huggingface.co/spaces/An-619/FastSAM

πŸ“• Paper: https://arxiv.org/pdf/2306.12156.pdf

πŸ”—Dataset: https://paperswithcode.com/dataset/sa-1b

https://t.iss.one/DataScienceT
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⭐️ LMFlow: An Extensible Toolkit for Finetuning and Inference of Large Foundation Models

Extensible and lightweight toolkit, LMFlow, which aims to simplify the finetuning and inference of general large foundation models.

πŸ–₯ Github: https://github.com/optimalscale/lmflow

⭐️ Demo: https://lmflow.com/

πŸ“• Paper: https://arxiv.org/abs/2306.12420v1

πŸ”—Dataset: https://paperswithcode.com/dataset/pubmedqa

Official channel:
https://t.iss.one/DataScienceM
Top Large Language Models based on the Elo rating, MT-Bench, and MMLU

https://t.iss.one/DataScienceT
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Automatically find issues in image datasets and practice data-centric computer vision.

CleanVision automatically detects potential issues in image datasets like images that are: blurry, under/over-exposed, (near) duplicates, etc. This data-centric AI package is a quick first step for any computer vision project to find problems in the dataset, which you want to address before applying machine learning. CleanVision is super simple -- run the same couple lines of Python code to audit any image dataset!

https://github.com/cleanlab/cleanvision

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The Attention Mechanism from Scratch

https://machinelearningmastery.com/the-attention-mechanism-from-scratch/

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Introduction to Computer Architecture, IIT Delhi

πŸ†“ Free Online Course
πŸ’» 38 Lecture Videos
⏰ 1 Module
πŸƒβ€β™‚οΈ Self paced
Teacher πŸ‘¨β€πŸ« : Prof. Anshul Kumar

πŸ”— https://nptel.ac.in/courses/106102062

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πŸ”₯ Awesome-Multimodal-Large-Language-Models

Latest Papers and Datasets on Multimodal Large Language Models, and Their Evaluation.

πŸ–₯ Github: https://github.com/bradyfu/awesome-multimodal-large-language-models

πŸ“• Paper: https://arxiv.org/abs/2306.13394v1

πŸ”—Dataset: https://paperswithcode.com/dataset/coco

https://t.iss.one/DataScienceT
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⚑ LightGlue. Local Feature Matching at Light Speed

LightGlue a lightweight feature matcher with high accuracy and adaptive pruning techniques, both in the width and depth of the network, for blazing fast inference.

git clone https://github.com/cvg/LightGlue.git && cd LightGlue
python -m pip install -e .


πŸ–₯ Github: https://github.com/cvg/lightglue

πŸ“• Paper: https://arxiv.org/abs/2306.13643v1

πŸ”—Dataset: https://paperswithcode.com/dataset/hpatches

https://t.iss.one/DataScienceT
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πŸšΆβ€β™‚οΈ MotionGPT: Human Motion
as Foreign Language

MotionGPT consists of a motion tokenizer responsible for converting raw motion data into discrete motion tokens, as well as a motion-aware language model that learns to understand the motion tokens from large language pre-training models by corresponding textual descriptions.

⏩ Project: https://motion-gpt.github.io/

πŸ–₯ Github: https://github.com/openmotionlab/motiongpt

πŸ“• Paper: https://arxiv.org/pdf/2306.14795.pdf

πŸ”—Dataset: https://paperswithcode.com/dataset/amass

https://t.iss.one/DataScienceT
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PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation

πŸ–₯ Github: https://github.com/jieqianyu/panet

⏩ Paper: https://arxiv.org/pdf/2306.15348v1.pdf

πŸ’¨ Dataset: https://paperswithcode.com/dataset/kitti

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