Nā hale waihona puke i kākau ʻia ma Jupyter Notebook
Interactive Parallel Computing with IPython
IPython Parallel: Interactive Parallel Computing ma Python.
- 2.4k
- GNU General Public License v3.0
stable-diffusion
Hōʻike kēia mana o CompVis/stable-diffusion i kahi palapala kauoha-line interactive e hoʻohui i ka text2img a me ka img2img hana i loko o kahi pānaehana "dream bot", he WebGUI, a me nā hiʻohiʻona he nui a me nā mea hoʻonui ʻē aʻe. [Neʻe i: https://github.com/invoke-ai/InvokeAI] (na lstein).
- 2.4k
- GNU General Public License v3.0
100-plus-Python-programming-exercises-extended
ʻO ka waihona ma kahi o 100+ python programming hoʻoikaika kino pilikia i kūkākūkā ʻia, wehewehe ʻia a hoʻoponopono ʻia ma nā ʻano like ʻole.
- 2.4k
mlops-course
E aʻo pehea e hoʻolālā, hoʻomohala, hoʻonohonoho a mālama i kahi noi ML hopena i ka hopena ma ka nui.
- 2.4k
- MIT
shapash
🔅 Shapash: Hiki ke wehewehe a me ka wehewehe ʻana i ka mea hoʻohana e hoʻomohala i nā kumu hoʻohālike aʻo mīkini hilinaʻi.
- 2.4k
- Apache License 2.0
diff-svc
ʻO ka hoʻololi ʻana i ka leo hīmeni ma o ke kumu hoʻohālike.
- 2.4k
- GNU Affero General Public License v3.0
3D-printed-mirror-array
3D hiki ke paʻi ʻia nā aniani aniani hexagonal hiki ke hoʻohālikelike i ka lā i nā ʻano like ʻole.
- 2.3k
- MIT
leetcode-company-wise-problems-2022
Loaʻa nā papa inoa o nā nīnau akamai ʻoihana ma ka leetcode premium. ʻO kēlā me kēia faila csv i loko o ka papa kuhikuhi ʻoihana e pili ana i kahi papa inoa o nā nīnau ma ka leetcode no kahi hui kikoʻī e pili ana i nā hōʻailona hui leetcode. Hoʻohou ʻia mai Mei, 2022..
- 2.3k
- MIT
whylogs
ʻO kahi waihona hoʻopaʻa ʻikepili kumu no nā kumu aʻo mīkini a me nā pipeline data. 📚 Hāʻawi i ka ʻike i ka maikaʻi o ka ʻikepili a me ka hana hoʻohālike i ka manawa. 🛡️ Kākoʻo i ka hōʻiliʻili ʻikepili mālama pilikino, hōʻoia i ka palekana a me ka paʻa. 📈.
- 2.3k
- Apache License 2.0
stability-sdk
SDK no ka launa pū ʻana me nā API stability.ai (e.g. stable diffusion inference).
- 2.3k
- MIT
Learning-Bitcoin-from-the-Command-Line
He papa piha no ke aʻo ʻana i ka polokalamu a me ka hoʻohana ʻana i Bitcoin mai ke kauoha [Neʻe i: https://github.com/BlockchainCommons/Learning-Bitcoin-from-the-Command-Line] (na ChristopherA).
- 2.3k
ML-foundations
Nā Kumu Aʻo Mīkini: Algebra Linear, Calculus, Statistics & Computer Science.
- 2.3k
- MIT
selfie
He ʻōnaehana polokalamu hoʻonaʻauao o kahi mea hōʻuluʻulu C hoʻohui ponoʻī liʻiliʻi, kahi emulator RISC-V e hoʻokō pono iā ia iho, a me kahi hypervisor RISC-V hoʻokipa ponoʻī liʻiliʻi.
- 2.3k
- BSD 2-clause "Simplified"
Kandinsky-2
Kandinsky 2 — ʻōlelo hoʻohālikelike latent diffusion kiʻi ʻōlelo2.
- 2.3k
- Apache License 2.0
Promptify
Enekinia koke | E hoʻohana i ka GPT a i ʻole nā hiʻohiʻona ʻē aʻe e pili ana i ka wikiwiki e kiʻi i ka hoʻopuka i kūkulu ʻia. E hui pū me kā mākou hoʻopaʻapaʻa no ka Prompt-Engineering, LLM a me nā noiʻi hou loa.
- 2.3k
- Apache License 2.0
qiskit-tutorials
He hōʻiliʻili o nā puke puke Jupyter e hōʻike ana pehea e hoʻohana ai i ka Qiskit SDK.
- 2.2k
- Apache License 2.0
An-Introduction-to-Statistical-Learning
Aia kēia waihona i nā hoʻomaʻamaʻa a me kāna hopena i loko o ka puke "An Introduction to Statistical Learning" ma python..
- 2.2k
datasets
🎁 4,800,000+ kiʻi Unsplash i loaʻa no ka noiʻi a me ke aʻo ʻana i nā mīkini (ma unsplash).
- 2.1k
coursera-deep-learning-specialization
Nā memo, nā haʻawina hoʻolālā a me nā nīnau nīnau mai nā papa āpau i loko o ka Coursera Deep Learning specialization i hāʻawi ʻia e deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Hoʻomaikaʻi i nā pūnaewele neural hohonu: Hyperparameter tuning, Regularization and Optimization; (iii) Hoʻonohonoho i nā papahana aʻo mīkini; (iv) Nā Pūnaewele Neural Convolutional; (v) Nā Hoʻohālike Kaʻina.
- 2.1k
pytorch-GAT
ʻO kaʻu hoʻokō ʻana i ka pepa GAT kumu (Veličković et al.). Ua hoʻokomo pū wau i ka faila playground.py no ka nānā ʻana i ka ʻikepili Cora, nā hoʻopili GAT, kahi ʻenehana nānā, a me nā histograms entropy. Ua kākoʻo au i nā laʻana ʻelua ʻo Cora (transductive) a me PPI (inductive)!.
- 2.1k
- MIT