zky001's repos on GitHub
1 人关注
AI-for-Keras
本系列代码主要是作者Python人工智能之Keras的系列博客,涉及回归神经网络、CNN、RNN、LSTM等内容。基础性代码,希望对您有所帮助。
1 人关注
APIJSON
🚀 零代码、热更新、全自动 ORM 库,后端接口和文档零代码,前端(客户端) 定制返回 JSON 的数据和结构。 🚀 A JSON Transmission Protocol and an ORM Library for automatically providing APIs and Docs.
1 人关注
awesome-notebooks
+100 awesome Jupyter Notebooks templates, organized by tools, published by the Naas community, to kickstart your data projects in minutes. 😎
0 人关注
3book
《Web安全之强化学习与GAN》
0 人关注
ADRepository-Anomaly-detection-datasets
ADRepository: Real-world anomaly detection datasets, including tabular data (categorical and numerical data), time series data, graph data, image data, and video data.
0 人关注
Agent-Smith
Agent Smith: A Single Image Can Jailbreak One Million Multimodal LLM Agents Exponentially Fast
0 人关注
agentscope
Start building LLM-empowered multi-agent applications in an easier way.
PHP · 0 人关注
AIP
基金定投辅助工具(automatic investment plan)
0 人关注
algo
数据结构和算法必知必会的50个代码实现
JavaScript · 0 人关注
AlphaGo
A replication of DeepMind's 2016 Nature publication, "Mastering the game of Go with deep neural networks and tree search," details of which can be found on their website.
Java · 0 人关注
ambrose
A platform for visualization and real-time monitoring of data workflows
JavaScript · 0 人关注
antSword
中国蚁剑是一款跨平台的开源网站管理工具
Go · 0 人关注
apns2
⚡HTTP/2 Apple Push Notification Service (APNs) push provider for Go — Send push notifications to iOS, tvOS, and OSX apps, using the new APNs HTTP/2 protocol.
Python · 0 人关注
AppleDNS
Apple 网络服务加速配置。真的快,快出声!(少数派、Appinn 推荐)
JavaScript · 0 人关注
aria2gui
Aria2GUI for MAC OS X
Python · 0 人关注
arpy
Mac OSX ARP spoof (MiTM) tool that can also plug into Gource
Python · 0 人关注
asciinema
Terminal session recorder
0 人关注
Auto-GPT
An experimental open-source attempt to make GPT-4 fully autonomous.
Python · 0 人关注
Auto-GPT-ZH
Auto-GPT中文版本及爱好者组织 同步更新原项目 AI领域创业 自媒体组织 用AI工作学习创作变现
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autocreate
Golang 全自动生成业务框架,原来需要1天的事情,现在只需要1分钟
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awesome-flask
A curated list of awesome Flask resources and plugins
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Awesome-Jailbreak-on-LLMs
Awesome-Jailbreak-on-LLMs is a collection of state-of-the-art, novel, exciting jailbreak methods on LLMs. It contains papers, codes, datasets, evaluations, and analyses.