جایگاه ۲ و ۳ این مقاله باقی مونده. از دوستان کسی خواست در خدمتم
@Raminmousa
@Raminmousa
DD-Net
👍 Github: https://github.com/fandulu/DD-Net
⚜️ Paper: https://arxiv.org/pdf/1907.09658.pdf
✅ Datasets: https://paperswithcode.com/dataset/gtea
@Machine_learn
@Machine_learn
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Final Edit-Sha.pdf
1.3 MB
Title: The IndRNN Capsule Approach for Persian Multi-Domain Sentiment Analysis
Authors:
ramin mousa
Mohammad Ali Dadgostarnia
Amir Olfati Malamiri
Elham Behnam
Shahram Miri Kelaniki
doi:10.22105/jarie.2023.345352.1477
@raminmousa
@Machine_learn
Authors:
ramin mousa
Mohammad Ali Dadgostarnia
Amir Olfati Malamiri
Elham Behnam
Shahram Miri Kelaniki
doi:10.22105/jarie.2023.345352.1477
@raminmousa
@Machine_learn
MalwareDetection.pdf
688.5 KB
Title: Combining machine learning and deep learning for Android malware detection
Authors:
@Raminmousa
Shahram Miri Kelaniki
link: https://www.researchgate.net/publication/374232656_Combining_machine_learning_and_deep_learning_for_Android_malware_detection
@Machine_learn
Authors:
@Raminmousa
Shahram Miri Kelaniki
link: https://www.researchgate.net/publication/374232656_Combining_machine_learning_and_deep_learning_for_Android_malware_detection
@Machine_learn
parallel_resnet_for_eye_angle_estimation2.pdf
504.7 KB
Title:Parallel Resnet for Eye Angle Estimation
Authors:
Ramin Mousa
Nastaran Aminian
Gholamreza Heidary
Nima Karimi
@Raminmousa
@Machine_learn
Authors:
Ramin Mousa
Nastaran Aminian
Gholamreza Heidary
Nima Karimi
@Raminmousa
@Machine_learn
SplitGNN
🖥 Github: https://github.com/blackboxo/SplitGNN
📕 Paper: https://dl.acm.org/doi/pdf/10.1145/3583780.3615067
🔥 Datasets: https://paperswithcode.com/dataset/fdcompcn
@Machine_learn
🖥 Github: https://github.com/blackboxo/SplitGNN
📕 Paper: https://dl.acm.org/doi/pdf/10.1145/3583780.3615067
🔥 Datasets: https://paperswithcode.com/dataset/fdcompcn
@Machine_learn
🦩 Woodpecker: Hallucination Correction for Multimodal Large Language Models
🖥 Github: https://github.com/bradyfu/woodpecker
📕 Paper: https://arxiv.org/abs/2310.15110v1
⏩ Demo: https://21527a47f03813481c.gradio.live/
@Machine_learn
🖥 Github: https://github.com/bradyfu/woodpecker
📕 Paper: https://arxiv.org/abs/2310.15110v1
⏩ Demo: https://21527a47f03813481c.gradio.live/
@Machine_learn
Machine learning books and papers
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…
با عرض سلام تخفيف ٧٠٪ دو پكيج يادگيري ماشين و عميق, براي كساني كه نتونستن تهيه كنند رو تا شب در نظر گرفتيم كسايي كه نياز دارن ميتونن به ايدي بنده پيام بدن.
@Raminmousa
@Raminmousa
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lbdl.pdf
4.4 MB
Book: The Little Book of
Deep Learning
Authors: François Fleuret
ISBN: Null
year: 2023
pages: 168
Tags:#DL
@Machine_learn
Deep Learning
Authors: François Fleuret
ISBN: Null
year: 2023
pages: 168
Tags:#DL
@Machine_learn
Human-Guided Complexity-Controlled Abstractions
🖥 Github: https://github.com/mycal-tucker/human-guided-abstractions
📕 Paper: https://arxiv.org/pdf/2310.17550v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/fashion-mnist
@Machine_learn
🖥 Github: https://github.com/mycal-tucker/human-guided-abstractions
📕 Paper: https://arxiv.org/pdf/2310.17550v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/fashion-mnist
@Machine_learn
🕵️ Detecting Pretraining Data from Large Language Models
🖥 Github: https://github.com/swj0419/detect-pretrain-code
📕 Paper: https://arxiv.org/pdf/2310.16789.pdf
📘 WikiMIA Benchmark:
⏩ Project: https://swj0419.github.io/detect-pretrain.github.io/
@Machine_learn
🖥 Github: https://github.com/swj0419/detect-pretrain-code
📕 Paper: https://arxiv.org/pdf/2310.16789.pdf
📘 WikiMIA Benchmark:
⏩ Project: https://swj0419.github.io/detect-pretrain.github.io/
@Machine_learn
DialogLLMScenic
🖥 Github: https://github.com/avmb/dialogllmscenic
📕 Paper: https://arxiv.org/pdf/2310.17372v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/carla
⭐ Tasks: https://paperswithcode.com/task/self-driving-cars
@Machine_learn
🖥 Github: https://github.com/avmb/dialogllmscenic
📕 Paper: https://arxiv.org/pdf/2310.17372v1.pdf
🔥 Datasets: https://paperswithcode.com/dataset/carla
⭐ Tasks: https://paperswithcode.com/task/self-driving-cars
@Machine_learn
Foundational-Python-for-Data-Science_bibis.ir.pdf
16.2 MB
Book: Foundation Python for Data Scientist
Authors: Kennedy R
ISBN: Null
year: 202
pages: 686
Tags:#Python
@Machine_learn
Authors: Kennedy R
ISBN: Null
year: 202
pages: 686
Tags:#Python
@Machine_learn
Bilingual Corpus Mining and Multistage Fine-Tuning for Improving Machine Translation of Lecture Transcripts
🖥 Github: https://github.com/shyyhs/CourseraParallelCorpusMining
📕 Paper: https://arxiv.org/abs/2311.03696v1
🔥 Datasets: https://paperswithcode.com/dataset/aspec
@Machine_learn
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⚡️ LLMRec: Large Language Models with Graph Augmentation for Recommendation
LLMRec - это новый фреймворк и датасет, улучшающий рекомендательные системы путем применения простых, но эффективных стратегий дополнения графов на основе LLM.
🖥 Github: https://github.com/hkuds/llmrec
📕 Paper: https://arxiv.org/abs/2311.00423v1
⏩ Project: https://llmrec.github.io/
🌐 Dataset: https://llmrec.github.io/#
@Machine_learn
LLMRec - это новый фреймворк и датасет, улучшающий рекомендательные системы путем применения простых, но эффективных стратегий дополнения графов на основе LLM.
🖥 Github: https://github.com/hkuds/llmrec
📕 Paper: https://arxiv.org/abs/2311.00423v1
⏩ Project: https://llmrec.github.io/
🌐 Dataset: https://llmrec.github.io/#
@Machine_learn
Deep Learning.pdf
47.3 MB
Book: Deep Learning Foundations and Concepts
Authors: Christopher M. Bishop
ISBN: 978-3-031-45468-4
year: 2023
pages: 656
Tags: #DL
@Machine_learn
Authors: Christopher M. Bishop
ISBN: 978-3-031-45468-4
year: 2023
pages: 656
Tags: #DL
@Machine_learn
🚀 Introducing YOLO-NAS Pose : A Game-Changer in Pose Estimation 🚀
🖥 Github: https://github.com/Deci-AI/super-gradients
📕 Notebook: https://colab.research.google.com/drive/1O4N5Vbzv0rfkT81LQidPktX8RtoS5A40
🚀 Demo: https://huggingface.co/spaces/Deci/YOLO-NAS-Pose-Demo
🌐 Colab: https://colab.research.google.com/drive/1agLj0aGx48C_rZPrTkeA18kuncack6lF
@Machine_learn
🖥 Github: https://github.com/Deci-AI/super-gradients
📕 Notebook: https://colab.research.google.com/drive/1O4N5Vbzv0rfkT81LQidPktX8RtoS5A40
🚀 Demo: https://huggingface.co/spaces/Deci/YOLO-NAS-Pose-Demo
🌐 Colab: https://colab.research.google.com/drive/1agLj0aGx48C_rZPrTkeA18kuncack6lF
@Machine_learn
✨ Feature Selection for Deep Tabular Models
🐱 Github: https://github.com/vcherepanova/tabular-feature-selection
📕 Paper: https://arxiv.org/pdf/2311.05877v1.pdf
⭐ Tasks: https://paperswithcode.com/task/feature-selection
@Machine_learn
🐱 Github: https://github.com/vcherepanova/tabular-feature-selection
📕 Paper: https://arxiv.org/pdf/2311.05877v1.pdf
⭐ Tasks: https://paperswithcode.com/task/feature-selection
@Machine_learn