Benchmarking Test-Time Adaptation against Distribution Shifts in Image Classification
🖥 Github: https://github.com/yuyongcan/benchmark-tta
⏩ Paper: https://arxiv.org/pdf/2307.03133v1.pdf
💨 Dataset: https://paperswithcode.com/imagenet
@Machine_learn
🖥 Github: https://github.com/yuyongcan/benchmark-tta
⏩ Paper: https://arxiv.org/pdf/2307.03133v1.pdf
💨 Dataset: https://paperswithcode.com/imagenet
@Machine_learn
Modeling and Simulation in Python.pdf
8.1 MB
Book: MODELING AND SIMULATION
IN PYTHON AN INTRODUSTENNINGERSCIENTISTS
Authors: Allen B. Downey
ISBN: 978-1-7185-0217-8
year: 2023
pages: 344
Tags:#Python #"Modeling
@Machine_learn
IN PYTHON AN INTRODUSTENNINGERSCIENTISTS
Authors: Allen B. Downey
ISBN: 978-1-7185-0217-8
year: 2023
pages: 344
Tags:#Python #"Modeling
@Machine_learn
با عرض سلام دو پکیچ یادگیری ماشین(یادگیری پایتون، تنسورفلو،کراس) و یادگیری عمیق پیشرفته با تخفیف ۷۰٪ برای دوستان گذاشتیم. جهت خرید می تونین به ایدی بنده پیام بدین.
@Raminmousa
@Raminmousa
🌆Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback
🖥 Github: https://github.com/tetrzim/diffusion-human-feedback
⏩ Paper: https://arxiv.org/pdf/2307.02770v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/imagenet
@Machine_learn
🖥 Github: https://github.com/tetrzim/diffusion-human-feedback
⏩ Paper: https://arxiv.org/pdf/2307.02770v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/imagenet
@Machine_learn
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AnimateDiff
Effective framework to animate most of existing personalized text-to-image models once for all, saving the efforts in model-specific tuning.
🖥 Github: https://github.com/guoyww/animatediff/
🖥 Colab: https://colab.research.google.com/github/camenduru/AnimateDiff-colab/blob/main/AnimateDiff_colab.ipynb
📕 Paper: https://arxiv.org/abs/2307.04725
🚀 Project: https://animatediff.github.io/
@Machine_learn
Effective framework to animate most of existing personalized text-to-image models once for all, saving the efforts in model-specific tuning.
🖥 Github: https://github.com/guoyww/animatediff/
🖥 Colab: https://colab.research.google.com/github/camenduru/AnimateDiff-colab/blob/main/AnimateDiff_colab.ipynb
📕 Paper: https://arxiv.org/abs/2307.04725
🚀 Project: https://animatediff.github.io/
@Machine_learn
Neural Video Depth Stabilizer (ICCV2023) 🚀🚀🚀
🖥 Github: https://github.com/raymondwang987/nvds
⏩ Paper: https://arxiv.org/pdf/2307.08695v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/wsvd
@Machine_learn
🖥 Github: https://github.com/raymondwang987/nvds
⏩ Paper: https://arxiv.org/pdf/2307.08695v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/wsvd
@Machine_learn
Forwarded from Eng. Hussein Sheikho 👨💻
This channels is for Programmers, Coders, Software Engineers.
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
✅ Data Science Channels:
https://www.tg-me.com/addlist/8_rRW2scgfRhOTc0
✅ Main Channel:
https://www.tg-me.com/DataScienceM
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
✅ Data Science Channels:
https://www.tg-me.com/addlist/8_rRW2scgfRhOTc0
✅ Main Channel:
https://www.tg-me.com/DataScienceM
FLASK: Fine-grained Language Model Evaluation Based on Alignment Skill Sets
🖥 Github: https://github.com/kaistai/flask
⏩ Paper: https://arxiv.org/pdf/2307.10928v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/gsm8k
@Machine_learn
🖥 Github: https://github.com/kaistai/flask
⏩ Paper: https://arxiv.org/pdf/2307.10928v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/gsm8k
@Machine_learn
Remote Bio-Sensing: Open Source Benchmark Framework for Fair Evaluation of rPPG
🖥 Github: https://github.com/remotebiosensing/rppg
📕 Paper: https://arxiv.org/abs/2307.12644v1
🔥 Dataset: https://paperswithcode.com/dataset/ubfc-rppg
@Machine_learn
🖥 Github: https://github.com/remotebiosensing/rppg
📕 Paper: https://arxiv.org/abs/2307.12644v1
🔥 Dataset: https://paperswithcode.com/dataset/ubfc-rppg
@Machine_learn
29733376.pdf
3.4 MB
Book: Test Your Skills In Python
SECOND EDITION
Authors: SHIVANI GOEL
ISBN: 978-93-5551-181-2
year: 2023
pages: 308
Tags:#Python
@Machine_learn
SECOND EDITION
Authors: SHIVANI GOEL
ISBN: 978-93-5551-181-2
year: 2023
pages: 308
Tags:#Python
@Machine_learn
Awesome-Align-LLM-Human
🖥 Github: https://github.com/garyyufei/alignllmhumansurvey
📕 Paper: https://arxiv.org/pdf/2307.12966v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/gsm8k
@Machine_learn
🖥 Github: https://github.com/garyyufei/alignllmhumansurvey
📕 Paper: https://arxiv.org/pdf/2307.12966v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/gsm8k
@Machine_learn
SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator
🖥 Github: https://github.com/czvvd/svdformer
⏩ Paper: https://arxiv.org/pdf/2307.08492v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/shapenet
@Machine_learn
🖥 Github: https://github.com/czvvd/svdformer
⏩ Paper: https://arxiv.org/pdf/2307.08492v1.pdf
💨 Dataset: https://paperswithcode.com/dataset/shapenet
@Machine_learn
🔥 Artificial Intelligence for Science (AIRS)
•OpenQM: AI for Quantum Mechanics
•OpenDFT: AI for Density Functional Theory
•OpenMol: AI for Small Molecules
•OpenProt: AI for Protein Science
•OpenMat: AI for Materials Science
•OpenMI: AI for Molecular Interactions
•OpenPDE: AI for Partial Differential Equations
🖥 Github: https://github.com/divelab/AIRS
📕 Paper: https://arxiv.org/abs/2307.08423
⭐️ Website: https://www.air4.science/
📌 Dataset: https://paperswithcode.com/dataset/atom3d
@Machine_learn
•OpenQM: AI for Quantum Mechanics
•OpenDFT: AI for Density Functional Theory
•OpenMol: AI for Small Molecules
•OpenProt: AI for Protein Science
•OpenMat: AI for Materials Science
•OpenMI: AI for Molecular Interactions
•OpenPDE: AI for Partial Differential Equations
🖥 Github: https://github.com/divelab/AIRS
📕 Paper: https://arxiv.org/abs/2307.08423
⭐️ Website: https://www.air4.science/
📌 Dataset: https://paperswithcode.com/dataset/atom3d
@Machine_learn
PG-RCNN: Semantic Surface Point Generation for 3D Object Detection (ICCV 2023)
🖥 Github: https://github.com/quotation2520/pg-rcnn
📕 Paper: https://arxiv.org/pdf/2307.12637v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/kitti
@Machine_learn
🖥 Github: https://github.com/quotation2520/pg-rcnn
📕 Paper: https://arxiv.org/pdf/2307.12637v1.pdf
🔥 Dataset: https://paperswithcode.com/dataset/kitti
@Machine_learn
Mathematics of Deep Learning.pdf
10.8 MB
Book: Mathematics of Deep Learning
Authors: Leonid Berlyand and Pierre-Emmanuel Jabin
ISBN: 978-3-11-102431-8
year: 2023
pages: 308
Tags:#Python
@Machine_learn
Authors: Leonid Berlyand and Pierre-Emmanuel Jabin
ISBN: 978-3-11-102431-8
year: 2023
pages: 308
Tags:#Python
@Machine_learn
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 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)
جهت تهیه می تونین به ایدی بنده مراجعه کنین
@Raminmousa
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)
جهت تهیه می تونین به ایدی بنده مراجعه کنین
@Raminmousa
Forwarded from Eng. Hussein Sheikho
This channels is for Programmers, Coders, Software Engineers.
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
✅ Data Science Channels:
https://www.tg-me.com/addlist/8_rRW2scgfRhOTc0
✅ Main Channel:
https://www.tg-me.com/DataScienceM
0- Python
1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning
8- programming Languages
✅ Data Science Channels:
https://www.tg-me.com/addlist/8_rRW2scgfRhOTc0
✅ Main Channel:
https://www.tg-me.com/DataScienceM