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/

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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.

🤗 Post: https://huggingface.co/blog/mms_adapters

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

🖥 Github: https://github.com/facebookresearch/fairseq/tree/main/examples/mms/asr

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

📕 Paper: https://huggingface.co/papers/2305.13516

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Building Transformer Models with Attention Crash Course. Build a Neural Machine Translator in 12 Days

https://machinelearningmastery.com/building-transformer-models-with-attention-crash-course-build-a-neural-machine-translator-in-12-days/

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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

🔥 Code: github.com/fahadshamshad/Clip2Protect

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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.

🖥 Github: https://github.com/optimalscale/lmflow

⭐️ Demo: https://lmflow.com/

📕 Paper: https://arxiv.org/abs/2306.12420v1

🔗Dataset: https://paperswithcode.com/dataset/pubmedqa

Official channel:
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Top Large Language Models based on the Elo rating, MT-Bench, and MMLU

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CBOGlobalConvergenceAnalysis

🖥 Github: https://github.com/efficienttraining/labelbench

⏩ Paper: https://arxiv.org/pdf/2306.09778v1.pdf

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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

🆓 Free Online Course
💻 38 Lecture Videos
⏰ 1 Module
🏃‍♂️ Self paced
Teacher 👨‍🏫 : Prof. Anshul Kumar

🔗 https://nptel.ac.in/courses/106102062

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🔥 Awesome-Multimodal-Large-Language-Models

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

🖥 Github: https://github.com/bradyfu/awesome-multimodal-large-language-models

📕 Paper: https://arxiv.org/abs/2306.13394v1

🔗Dataset: https://paperswithcode.com/dataset/coco

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🗒 Machine Learning Cheat Sheets

https://sites.google.com/view/datascience-cheat-sheets

Machine Learning Animations: https://sites.google.com/view/mlingifs#h.341bzfgiuxfx

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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 .

🖥 Github: https://github.com/cvg/lightglue

📕 Paper: https://arxiv.org/abs/2306.13643v1

🔗Dataset: https://paperswithcode.com/dataset/hpatches

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This channel is for Programmers, Coders, Software Engineers.

1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning

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🚶‍♂️ 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 denoscriptions.

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

🖥 Github: https://github.com/openmotionlab/motiongpt

📕 Paper: https://arxiv.org/pdf/2306.14795.pdf

🔗Dataset: https://paperswithcode.com/dataset/amass

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🖥 Free Courses on Large Language Models

▪ChatGPT Prompt Engineering for Developers

▪LangChain for LLM Application Development

▪Building Systems with the ChatGPT API

▪Google Cloud Generative AI Learning Path

▪Introduction to Large Language Models with Google Cloud

▪LLM University

▪Full Stack LLM Bootcamp

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PANet: LiDAR Panoptic Segmentation with Sparse Instance Proposal and Aggregation

🖥 Github: https://github.com/jieqianyu/panet

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

💨 Dataset: https://paperswithcode.com/dataset/kitti

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💬 3D-Speaker: A Large-Scale Multi-Device, Multi-Distance, and Multi-Dialect Corpus for Speech Representation Disentanglement

A large-scale speech corpus to facilitate the research of speech representation

🖥 Github: https://github.com/alibaba-damo-academy/3D-Speaker

📕 Paper: https://arxiv.org/abs/2306.15354v1

🔗Dataset: https://3dspeaker.github.io/

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