neuronalenetze-en-zeta2-2col-dkrieselcom.pdf
5.6 MB
Book: A brief introduction to Neural Networks
Authors: David Kriesel
ISBN: Null
year: 2005
pages: 242
Tags: #ANN
@Machine_learn
Authors: David Kriesel
ISBN: Null
year: 2005
pages: 242
Tags: #ANN
@Machine_learn
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Hyperparameter Optimization and Combined Data Sampling Techniques in Machine Learning for Customer Churn Prediction: A Comparative Analysis
📕 Paper: https://www.preprints.org/manuscript/202308.1478/v4
🔥 Dataset: https://www.kaggle.com/code/rinichristy/customer-churn-prediction-2020
@Machine_learn
📕 Paper: https://www.preprints.org/manuscript/202308.1478/v4
🔥 Dataset: https://www.kaggle.com/code/rinichristy/customer-churn-prediction-2020
@Machine_learn
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🇺🇿 Introducing Emu Video and Emu Edit, our latest generative AI research milestones
🚀 Blog: https://ai.meta.com/blog/emu-text-to-video-generation-image-editing-research/
⭐️Project page: https://emu-edit.metademolab.com
📌Paper: https://emu-edit.metademolab.com/assets/emu_edit.pdf
@Machine_learn
🚀 Blog: https://ai.meta.com/blog/emu-text-to-video-generation-image-editing-research/
⭐️Project page: https://emu-edit.metademolab.com
📌Paper: https://emu-edit.metademolab.com/assets/emu_edit.pdf
@Machine_learn
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🪐 ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems
🐱 Github: https://github.com/stanford-futuredata/ares
📕 Paper: https://arxiv.org/abs/2311.09476
⏩ Dataset: https://paperswithcode.com/dataset/kilt
@Machine_learn
🐱 Github: https://github.com/stanford-futuredata/ares
📕 Paper: https://arxiv.org/abs/2311.09476
⏩ Dataset: https://paperswithcode.com/dataset/kilt
@Machine_learn
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🌦 Makani: Massively parallel training of machine-learning based weather and climate models
🐱Github: https://github.com/NVIDIA/makani
📕Blog: https://developer.nvidia.com/blog/modeling-earths-atmosphere-with-spherical-fourier-neural-operators/
⏩Dataset: https://github.com/NVIDIA/makani/tree/main/datasets
@Machine_learn
🐱Github: https://github.com/NVIDIA/makani
📕Blog: https://developer.nvidia.com/blog/modeling-earths-atmosphere-with-spherical-fourier-neural-operators/
⏩Dataset: https://github.com/NVIDIA/makani/tree/main/datasets
@Machine_learn
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💥 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
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🐬 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
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♟ 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
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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…»
dm.pdf
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
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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
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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
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♟ 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
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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
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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
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