TGINSIGHT SIMILAR POSTS
Source channel @githubtrending · Post #15248 · Oct 25
#java#awesome#backend#computer_science#distributed_systems#high_level_design#hld#interview#interview_questions#scalability#system_design You can learn important system design concepts for free, covering topics like scalability, availability, CAP theorem, caching, databases, APIs, microservices, and distributed systems. This resource offers clear explanations, interview preparation guides, and practical design problems from easy to hard, helping you understand how to build reliable, scalable software systems. It also provides links to courses, books, newsletters, and videos to deepen your knowledge. Using these materials can improve your skills for system design interviews and real-world software architecture, making you more confident and effective in designing complex systems. https://github.com/ashishps1/awesome-system-design-resources
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@R4marketing · Post #806 · 08/13/2021, 08:00 AM
Совсем лайтовая статья для новичков "10 главных конструкций языка R". Содержание: - Комментарии - Переменные и векторы - Внешние модули - Ввод и вывод - Присваивание и сравнение - Условный оператор if - Цикл for - Функции - Классы, методы и объекты #статьи #easy
@testflightynoti · Post #37780 · 05/07/2026, 08:30 PM
#Futubull#Easy#Investment Join the Futubull-Easy Investment beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/LXJdcvBn Shared by Dimitri
@WangZhuanZhan · Post #34299 · 10/23/2024, 12:23 PM
X-x喜x乐l长c安a- 喜乐长安 (2016) 直达链接：https://pan.quark.cn/s/4723d3f85101 #喜乐长安 #长安乱 #Easy Life 链接：https://link3.cc/sf_com #电影#喜剧#台湾#10年代
@wangzhuanzhan · Post #33280 · 09/23/2024, 06:10 AM
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@WangZhuanZhan · Post #34066 · 10/15/2024, 05:50 AM
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@wangzhuanzhan · Post #32222 · 09/03/2024, 08:49 AM
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@testflightynoti · Post #37748 · 05/07/2026, 08:21 AM
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@githubtrending · Post #15433 · 01/23/2026, 02:30 PM
#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles. https://github.com/OpenBMB/UltraRAG