An awesome list of events and fellowship opportunities for Computer Science students
- computer-science-students
- data-science
- fellowship
- mooc
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An awesome list of events and fellowship opportunities for Computer Science students
ShadowsocksR update rss, SSR organization https://github.com/shadowsocksr
Your First AI Agents Company
Cartography is a Python tool that pulls infrastructure assets and their relationships into a Neo4j graph database.
Web-based SQLite database browser written in Python
All the controls missing in WPF. Over 1 million downloads.
Valet lets you securely store data in the iOS, tvOS, watchOS, or macOS Keychain without knowing a thing about how the Keychain works. It’s easy. We promise.
STUMPY is a powerful and scalable Python library for modern time series analysis
📦 CMake's missing package manager. A small CMake script for setup-free, cross-platform, reproducible dependency management.
An idiomatic Go (golang) validation package. Supports configurable and extensible validation rules (validators) using normal language constructs instead of error-prone struct tags.
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
📈 目前最大的工业缺陷检测数据库及论文集 Constantly summarizing open source dataset and critical papers in the field of surface defect research which are of great importance.
Vision infrastructure to turn complex documents into LLM-ready data
A library for bulk insertion of data into your database using ActiveRecord.
LCN distributed transaction framework, compatible with dubbo, spring cloud and Motan framework, supports various relational databases
A transactional, relational-graph-vector database that uses Datalog for query. The hippocampus for AI!
Blazing fast concurrent HashMap for Rust.
Downloads albums from the web in bulk for archive purposes
The Apache Tika toolkit detects and extracts metadata and text from over a thousand different file types (such as PPT, XLS, and PDF).
☑️ JavaScript fluent validation library
Sync MySQL data into elasticsearch
An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them.
标注自己的数据集,训练、评估、测试、部署自己的人工智能算法
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