💥 Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
🐱Github: https://github.com/PKU-YuanGroup/Video-LLaVA
🤗Demo: https://huggingface.co/spaces/LanguageBind/Video-LLaVA
📕Paper: https://arxiv.org/abs/2311.10122v1
⏩Dataset: https://paperswithcode.com/dataset/mmbench
@Machine_learn
🐱Github: https://github.com/PKU-YuanGroup/Video-LLaVA
🤗Demo: https://huggingface.co/spaces/LanguageBind/Video-LLaVA
📕Paper: https://arxiv.org/abs/2311.10122v1
⏩Dataset: https://paperswithcode.com/dataset/mmbench
@Machine_learn
🐬 ShareGPT4V:Improving Large Multi-Modal Models with Better Captions
🖥 Code: https://github.com/InternLM/InternLM-XComposer/tree/main/projects/ShareGPT4V
🦾 Project: https://sharegpt4v.github.io/
⚡️ Demo: https://huggingface.co/spaces/Lin-Chen/ShareGPT4V-7B
📚 Paper: https://arxiv.org/pdf/2311.12793.pdf
🔗 Dataset: https://huggingface.co/datasets/Lin-Chen/ShareGPT4V
@Machine_learn
🖥 Code: https://github.com/InternLM/InternLM-XComposer/tree/main/projects/ShareGPT4V
🦾 Project: https://sharegpt4v.github.io/
⚡️ Demo: https://huggingface.co/spaces/Lin-Chen/ShareGPT4V-7B
📚 Paper: https://arxiv.org/pdf/2311.12793.pdf
🔗 Dataset: https://huggingface.co/datasets/Lin-Chen/ShareGPT4V
@Machine_learn
🗣 HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation by Hierarchical Variational Inference for Zero-shot Speech Synthesis
🖥 Code: https://github.com/sh-lee-prml/hierspeechpp
🦾 Checkpoint: https://drive.google.com/drive/folders/1-L_90BlCkbPyKWWHTUjt5Fsu3kz0du0w?usp=sharing
⚡️ Demo: https://sh-lee-prml.github.io/HierSpeechpp-demo/
📚 Paper: https://arxiv.org/abs/2311.12454v1
🔗 Dataset: https://paperswithcode.com/dataset/libri-light
@Machine_learn
🖥 Code: https://github.com/sh-lee-prml/hierspeechpp
🦾 Checkpoint: https://drive.google.com/drive/folders/1-L_90BlCkbPyKWWHTUjt5Fsu3kz0du0w?usp=sharing
⚡️ Demo: https://sh-lee-prml.github.io/HierSpeechpp-demo/
📚 Paper: https://arxiv.org/abs/2311.12454v1
🔗 Dataset: https://paperswithcode.com/dataset/libri-light
@Machine_learn
♟ ChessVision - A dataset for logically coherent multi-label classification.
🖥 Github: https://github.com/espressovi/chessvisionchallenge
📕 Paper: https://arxiv.org/pdf/2311.12610v1.pdf
✨ Tasks: https://paperswithcode.com/task/classification-1
@Machine_learn
🖥 Github: https://github.com/espressovi/chessvisionchallenge
📕 Paper: https://arxiv.org/pdf/2311.12610v1.pdf
✨ Tasks: https://paperswithcode.com/task/classification-1
@Machine_learn
Infant Action Recognition
🖥 Github: https://github.com/ostadabbas/video-based-infant-action-recognition
📕 Paper: https://arxiv.org/pdf/2311.12300v1.pdf
✨ Tasks: https://paperswithcode.com/task/action-recognition-in-videos
🔥Datasets: https://paperswithcode.com/dataset/ntu-rgb-d
@Machine_learn
🖥 Github: https://github.com/ostadabbas/video-based-infant-action-recognition
📕 Paper: https://arxiv.org/pdf/2311.12300v1.pdf
✨ Tasks: https://paperswithcode.com/task/action-recognition-in-videos
🔥Datasets: https://paperswithcode.com/dataset/ntu-rgb-d
@Machine_learn
1: introduction to machine learning
2: Regression (linear and non-linear)
3: Tensorflow introduction
4: Tensorflow computaion graph
5: Tensorflow optimizer and loss function
6: Tensorflow linear and non linear regression
7: logistic regression
8: Tensorflow regression
___________
9: introduction to traditional machine learning
*10: knn and desicion tree
*11: desicion tree and Naive bayes
*12: desicion tree, knn, Naive bayes implementation
*13: k-means
*14: Guassion Mixture Model(GMM)
*15: implementation K-means and GMM
_
16: introduction to Artificial Neural Network
17: Multi-level Neural Network
18: Introduction to Convolution Neural Network
19: Tensorflow Multi-level Neural Network
20:Tensorflow CNN
21:CNN image clasaification
22: Cnn text clasaification
23: Recurrent Neural Network(RNN)
@Raminmousa
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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…»
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12.2 MB
Book: Algorithms for Decision Making
Authors: Mykel J. Kochenderfer ,Tim A. Wheeler
,Kyle H. Wray
ISBN: Null
year: 2022
pages: 700
Tags:#Decision making
@Machine_learn
Authors: Mykel J. Kochenderfer ,Tim A. Wheeler
,Kyle H. Wray
ISBN: Null
year: 2022
pages: 700
Tags:#Decision making
@Machine_learn
CSMeD: Citation Screening Meta-Dataset for systematic review automation evaluation
🖥 Github: https://github.com/wojciechkusa/systematic-review-datasets
📕 Paper: https://arxiv.org/pdf/2311.12474v1.pdf
✨ Tasks: https://paperswithcode.com/task/question-answering
🔥Datasets: https://paperswithcode.com/dataset/blurb
@Machine_learn
🖥 Github: https://github.com/wojciechkusa/systematic-review-datasets
📕 Paper: https://arxiv.org/pdf/2311.12474v1.pdf
✨ Tasks: https://paperswithcode.com/task/question-answering
🔥Datasets: https://paperswithcode.com/dataset/blurb
@Machine_learn
🔥 Diffusion360: Seamless 360 Degree Panoramic Image Generation based on Diffusion Models.
🖥 Code: https://github.com/archerfmy/sd-t2i-360panoimage
📚 Paper: https://arxiv.org/abs/2311.13141v1
🔗 Dataset: https://paperswithcode.com/dataset/sun360
@Machine_learn
🖥 Code: https://github.com/archerfmy/sd-t2i-360panoimage
📚 Paper: https://arxiv.org/abs/2311.13141v1
🔗 Dataset: https://paperswithcode.com/dataset/sun360
@Machine_learn
Probabilistic-Forecast-Reconciliation-with-DL
🖥 Github: https://github.com/guanyu0316/Probabilistic-Forecast-Reconciliation-with-DL
📕 Paper: https://arxiv.org/pdf/2311.12279v1.pdf
✨ Tasks: https://paperswithcode.com/task/time-series-1
@Machine_learn
🖥 Github: https://github.com/guanyu0316/Probabilistic-Forecast-Reconciliation-with-DL
📕 Paper: https://arxiv.org/pdf/2311.12279v1.pdf
✨ Tasks: https://paperswithcode.com/task/time-series-1
@Machine_learn
♟ ChessVision - A dataset for logically coherent multi-label classification.
🖥 Github: https://github.com/espressovi/chessvisionchallenge
📕 Paper: https://arxiv.org/abs/2311.12610
🔥Datasets: https://zenodo.org/records/8278015
@Machine_learn
🖥 Github: https://github.com/espressovi/chessvisionchallenge
📕 Paper: https://arxiv.org/abs/2311.12610
🔥Datasets: https://zenodo.org/records/8278015
@Machine_learn
Hyperparameter Optimization and Combined Data Sampling Techniques in Machine Learning for Customer Churn Prediction: A Comparative Analysis
📕 Paper: https://www.mdpi.com/2227-7080/11/6/167
🔥 Dataset: https://www.kaggle.com/code/rinichristy/customer-churn-prediction-2020
@Machine_learn
📕 Paper: https://www.mdpi.com/2227-7080/11/6/167
🔥 Dataset: https://www.kaggle.com/code/rinichristy/customer-churn-prediction-2020
@Machine_learn
BatchER
🖥 Github: https://github.com/fmh1art/batcher
📕 Paper: https://arxiv.org/pdf/2312.03987v1.pdf
✨ Tasks: https://paperswithcode.com/task/data-integration
@Machine_learn
🖥 Github: https://github.com/fmh1art/batcher
📕 Paper: https://arxiv.org/pdf/2312.03987v1.pdf
✨ Tasks: https://paperswithcode.com/task/data-integration
@Machine_learn
Syn-Rep-Learn
🖥 Github: https://github.com/google-research/syn-rep-learn
📕 Paper: https://arxiv.org/pdf/2312.04567v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/imagenet
@Machine_learn
🖥 Github: https://github.com/google-research/syn-rep-learn
📕 Paper: https://arxiv.org/pdf/2312.04567v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/imagenet
@Machine_learn
با عرض سلام این مقاله تا دو روز دیگه سابیمت میشه و ارکایوش هم تا ۱۵ روز دیگه چاد میشه. تنها دوجایگاه ازش باقی مونده...!
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🥇 TokenCompose, a text-to-image latent diffusion model trained with fine-grained grounding objectives
🖥 Code: https://github.com/mlpc-ucsd/TokenCompose
🏆 Website: https://mlpc-ucsd.github.io/TokenCompose/
📚 Paper: https://huggingface.co/papers/2312.03626
@Machine_learn
🖥 Code: https://github.com/mlpc-ucsd/TokenCompose
🏆 Website: https://mlpc-ucsd.github.io/TokenCompose/
📚 Paper: https://huggingface.co/papers/2312.03626
@Machine_learn
Exploring the potential of channel interactions for image restoration
🖥 Github: https://github.com/c-yn/ChaIR
📕 Paper: https://www.sciencedirect.com/science/article/abs/pii/S0950705123009061
🔥 Dataset: https://paperswithcode.com/dataset/reside
✨ Tasks: https://paperswithcode.com/task/deblurring
@Machine_learn
🖥 Github: https://github.com/c-yn/ChaIR
📕 Paper: https://www.sciencedirect.com/science/article/abs/pii/S0950705123009061
🔥 Dataset: https://paperswithcode.com/dataset/reside
✨ Tasks: https://paperswithcode.com/task/deblurring
@Machine_learn