Machine learning books and papers pinned «با عرض سلام دو پکیچ یادگیری ماشین و یادگیری عمیق را برای دوستانی که می خواهند تا فرداشب با تخفیف ۵۰٪ مجدد قرار دادیم این تخفیف اخرین سری از تخفیف های این دو پکیچ می باشد 1: introduction to machine learning 2: Regression (linear and non-linear) 3: Tensorflow…»
CreativeSynth: Creative Blending and Synthesis of Visual Arts based on Multimodal Diffusion
🖥 Github: https://github.com/haha-lisa/creativesynth
📕 Paper: https://arxiv.org/pdf/2401.14066v1.pdf
✨ Tasks: https://paperswithcode.com/task/image-generation
@Machine_learn
🖥 Github: https://github.com/haha-lisa/creativesynth
📕 Paper: https://arxiv.org/pdf/2401.14066v1.pdf
✨ Tasks: https://paperswithcode.com/task/image-generation
@Machine_learn
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🥳FreeInit with AnimateDiff Gradio Colab
🖥 colab: https://github.com/camenduru/FreeInit-colab
🔮page: https://tianxingwu.github.io/pages/FreeInit/
📚paper: https://arxiv.org/abs/2312.07537
🥩code: https://github.com/TianxingWu/FreeInit
@Machie_learn
🖥 colab: https://github.com/camenduru/FreeInit-colab
🔮page: https://tianxingwu.github.io/pages/FreeInit/
📚paper: https://arxiv.org/abs/2312.07537
🥩code: https://github.com/TianxingWu/FreeInit
@Machie_learn
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🔍 FIND: Interface Foundation Models' Embeddings
🖥 Code: https://github.com/UX-Decoder/FIND
🎓 Demo: http://find.xyzou.net/
🔮 Project Page: https://x-decoder-vl.github.io
🥩 Demo: http://find.xyzou.net
📚 ArXiv: https://arxiv.org/pdf/2312.07532.pdf
@Machine_learn
🖥 Code: https://github.com/UX-Decoder/FIND
🎓 Demo: http://find.xyzou.net/
🔮 Project Page: https://x-decoder-vl.github.io
🥩 Demo: http://find.xyzou.net
📚 ArXiv: https://arxiv.org/pdf/2312.07532.pdf
@Machine_learn
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pix2gestalt: Amodal Segmentation by Synthesizing Wholes
🖥 Github: https://github.com/cvlab-columbia/pix2gestalt
📕 Paper: https://arxiv.org/pdf/2401.14398v1.pdf
✨ Tasks: https://paperswithcode.com/task/3d-reconstruction
@Machine_learn
🖥 Github: https://github.com/cvlab-columbia/pix2gestalt
📕 Paper: https://arxiv.org/pdf/2401.14398v1.pdf
✨ Tasks: https://paperswithcode.com/task/3d-reconstruction
@Machine_learn
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🌪 Can machine learning predict chaos?
https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.5.043252
@Machine_learn
https://journals.aps.org/prresearch/abstract/10.1103/PhysRevResearch.5.043252
@Machine_learn
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🌠AnyDoor: Zero-shot Object-level Image Customization
🖥 Code: https://github.com/damo-vilab/AnyDoor
🎓 HF: https://huggingface.co/spaces/xichenhku/AnyDoor-online
🔮 Project Page: https://damo-vilab.github.io/AnyDoor-Page/
📚 ArXiv: https://arxiv.org/abs/2307.09481
@Machine_learn
pip install git+https://github.com/cocodataset/panopticapi.git
pip install pycocotools -i https://pypi.douban.com/simple
pip install lvis
🖥 Code: https://github.com/damo-vilab/AnyDoor
🎓 HF: https://huggingface.co/spaces/xichenhku/AnyDoor-online
🔮 Project Page: https://damo-vilab.github.io/AnyDoor-Page/
📚 ArXiv: https://arxiv.org/abs/2307.09481
@Machine_learn
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🌹4DGen: Grounded 4D Content Generation with Spatial-temporal Consistency
🖥 Code: https://github.com/VITA-Group/4DGen
🔮 Project: https://vita-group.github.io/4DGen/
📚 ArXiv: https://arxiv.org/abs/2305.06456
@Machine_learn
🖥 Code: https://github.com/VITA-Group/4DGen
🔮 Project: https://vita-group.github.io/4DGen/
📚 ArXiv: https://arxiv.org/abs/2305.06456
@Machine_learn
Vaccine: Perturbation-aware Alignment for Large Language Model
🖥 Github: https://github.com/git-disl/vaccineT
📕 Paper: https://arxiv.org/pdf/2402.01109v1.pdf
🔥Datasets: https://paperswithcode.com/dataset/sst
✨ Tasks: https://paperswithcode.com/task/language-modelling
@Machine_learn
🖥 Github: https://github.com/git-disl/vaccineT
📕 Paper: https://arxiv.org/pdf/2402.01109v1.pdf
🔥Datasets: https://paperswithcode.com/dataset/sst
✨ Tasks: https://paperswithcode.com/task/language-modelling
@Machine_learn
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🔥Physics-based Text-to-Motion🔥
🖥 Code: github.com/jiawei-ren/insactor
📚 Paper: arxiv.org/abs/2312.17135
⚡️ Project: https://jiawei-ren.github.io/projects/insactor/
@Machine_learn
🖥 Code: github.com/jiawei-ren/insactor
📚 Paper: arxiv.org/abs/2312.17135
⚡️ Project: https://jiawei-ren.github.io/projects/insactor/
@Machine_learn
OReilly.Training.Data.for.Machine.Learning.pdf
21.3 MB
Book: 📚Training Data for Machine Learning: Human Supervision from Annotation to Data Science (2023)
Authors: Anthony Sarkis
ISBN: null
year: 2023
pages: 332
Tags: #Machine_learning#Data
@Machine_learn
Authors: Anthony Sarkis
ISBN: null
year: 2023
pages: 332
Tags: #Machine_learning#Data
@Machine_learn
💊 AMIE: A research AI system for diagnostic medical reasoning and conversations
💡 Blog: https://blog.research.google/2024/01/amie-research-ai-system-for-diagnostic_12.html
📚 Paper: https://arxiv.org/abs/2401.05654
@Machine_learn
💡 Blog: https://blog.research.google/2024/01/amie-research-ai-system-for-diagnostic_12.html
📚 Paper: https://arxiv.org/abs/2401.05654
@Machine_learn
TimesFM is a forecasting model, pre-trained on a large time-series corpus of 100 billion real world time-points
https://blog.research.google/2024/02/a-decoder-only-foundation-model-for.html
@Machine_learn
https://blog.research.google/2024/02/a-decoder-only-foundation-model-for.html
@Machine_learn
📷 InstructIR: High-Quality Image Restoration Following Human Instructions
🖥 Code: https://github.com/mv-lab/InstructIR
🚀 Project: mv-lab.github.io/InstructIR/
🎮 Colab: https://colab.research.google.com/drive/1OrTvS-i6uLM2Y8kIkq8ZZRwEQxQFchfq
📚 Paper: https://arxiv.org/abs/2401.16468
@Machine_learn
🖥 Code: https://github.com/mv-lab/InstructIR
🚀 Project: mv-lab.github.io/InstructIR/
🎮 Colab: https://colab.research.google.com/drive/1OrTvS-i6uLM2Y8kIkq8ZZRwEQxQFchfq
📚 Paper: https://arxiv.org/abs/2401.16468
@Machine_learn
SoftEDA: Rethinking Rule-Based Data Augmentation with Soft Labels
🖥 Github: https://github.com/IIPL-CAU/SoftEDA
📕 Paper: https://arxiv.org/pdf/2402.05591v1.pdf
🔥Datasets: https://paperswithcode.com/dataset/cola
@Machine_learn
🖥 Github: https://github.com/IIPL-CAU/SoftEDA
📕 Paper: https://arxiv.org/pdf/2402.05591v1.pdf
🔥Datasets: https://paperswithcode.com/dataset/cola
@Machine_learn
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⭐️ YOLO-World Real-Time Open-Vocabulary Object Detection
🖥 Github: https://github.com/AILab-CVC/YOLO-World
📚 Paper: https://arxiv.org/abs/2401.17270
⚡️Demo: https://www.yoloworld.cc
🤗Hf: https://huggingface.co/spaces/stevengrove/YOLO-World
@Machine_learn
🖥 Github: https://github.com/AILab-CVC/YOLO-World
📚 Paper: https://arxiv.org/abs/2401.17270
⚡️Demo: https://www.yoloworld.cc
🤗Hf: https://huggingface.co/spaces/stevengrove/YOLO-World
@Machine_learn
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⚡️ LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation
🖥 Github: https://github.com/3DTopia/LGM
📚 Paper: https://arxiv.org/abs/2402.05054
🔗 Demo: https://huggingface.co/spaces/ashawkey/LGM
💻 Weights: https://huggingface.co/ashawkey/LGM
⏩ Project: https://me.kiui.moe/lgm/
@Machine_learn
🖥 Github: https://github.com/3DTopia/LGM
📚 Paper: https://arxiv.org/abs/2402.05054
🔗 Demo: https://huggingface.co/spaces/ashawkey/LGM
💻 Weights: https://huggingface.co/ashawkey/LGM
⏩ Project: https://me.kiui.moe/lgm/
@Machine_learn
EasyKV
🖥 Github: https://github.com/drsy/easykv
📕 Paper: https://arxiv.org/pdf/2402.06262v1.pdf
🔥Datasets: https://paperswithcode.com/dataset/webtext
@Machine_learn
🖥 Github: https://github.com/drsy/easykv
📕 Paper: https://arxiv.org/pdf/2402.06262v1.pdf
🔥Datasets: https://paperswithcode.com/dataset/webtext
@Machine_learn