Aclanthology البدائل & المنافسين

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ACL Anthology - ACL Anthology.


البدائل والمنافسين ل aclanthology.org من حيث المحتوى وحركة المرور والهيكل

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Papers With Code highlights trending Machine Learning research and the code to implement it.

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20,742 13K
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Promoting openness in scientific communication and the peer-review process

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NeurIPS 2024.

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1,297 712
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We’re on a journey to advance and democratize artificial intelligence through open source and open science.

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ACL Member Portal | The Association for Computational Linguistics Member Portal.

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An open source machine learning framework that accelerates the path from research prototyping to production deployment.

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The Computer Vision Foundation – A non-profit organization that fosters and supports research in all aspects of computer vision.

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NeurIPS 2024.

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796.8K 346.3K

AAAI advances the understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines.

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Weights & Biases, developer tools for machine learning

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An end-to-end open source machine learning platform for everyone. Discover TensorFlow's flexible ecosystem of tools, libraries and community resources.

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Why NumPy? Powerful n-dimensional arrays. Numerical computing tools. Interoperable. Performant. Open source.

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Fast.ai – fast.ai—Making neural nets uncool again.

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Keras documentation

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Journal of Machine Learning Research.

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ICML 2024.

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129K 50K

The all-in-one platform for AI development. Code together. Prototype. Train. Scale. Serve. From your browser - with zero setup. From the creators of PyTorch Lightning.

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Welcome to IJCAI | IJCAI.

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Log, organize, compare, register, and share all your ML model metadata in a single place.

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Pytorch-lightning.readthedocs.io is ranked number 10M in the world.

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Helping developers, students, and researchers master Computer Vision, Deep Learning, and OpenCV.

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31,628 519
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1.3M 133.3K

Making developers awesome at machine learning.

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4,154 434
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Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals.

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Accelerate AI training, power complex simulations, and render faster with NVIDIA H100 GPUs on Paperspace. Easy setup, cost-effective cloud compute.

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Course materials and notes for Stanford class CS231n: Convolutional Neural Networks for Visual Recognition.

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Code faster with Kite’s AI-powered autocomplete plugin for over 16 programming languages and 16 IDEs, featuring Multi-Line Completions. Works 100% locally.

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Scikit-learn: machine learning in Python — scikit-learn 0.16.1 documentation.

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Matplotlib — Visualization with Python.

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PyData |.

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Why SciPy? Fundamental algorithms. Broadly applicable. Foundational. Interoperable. Performant. Open source.

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Project Euclid

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Site not found · GitHub Pages.

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ICLR 2024.

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Faroit.

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Scale your compute-intensive Python workloads. From reinforcement learning to large-scale model serving, Ray makes the power of distributed compute easy and accessible to every engineer.

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Spell.ml is ranked number 10M in the world.

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Site not found · GitHub Pages.

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Your home for data science. A Medium publication sharing concepts, ideas and codes.

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Analytics India Magazine chronicles technological progress in the space of analytics, artificial intelligence, data science & big data in India

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Analytics Vidhya - Learn Machine learning, artificial intelligence, business analytics, data science, big data, data visualizations tools and techniques.

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662,164 82K
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Scipy Lecture Notes — Scipy lecture notes.

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Dive into Deep Learning — Dive into Deep Learning 1.0.3 documentation.

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Learn Deep Learning and Artificial Intelligence

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Learn Computer Vision, Deep Learning with OpenCV, PyTorch, Keras, & Tensorflow: Code + Tutorials

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47,679 15K
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913.5K 200.7K

With just a few dozen example images, you can train a working, state-of-the-art computer vision model in less than 24 hours

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Effortlessly build and scale your AI project, backed by world-class GPUs trusted by more than 500K builders.

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OpenCV provides a real-time optimized Computer Vision library, tools, and hardware. It also supports model execution for Machine Learning (ML) and Artificial Intelligence (AI).

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