Welcome to the comprehensive, community-driven resource repository for GATE Computer Science & Information Technology (CS & IT) 2027 aspirants. Securing a top rank in the Graduate Aptitude Test in Engineering (GATE) unlocks direct admissions to premier postgraduate programs (M.Tech/Ph.D.) at IITs, NITs, and IISc, alongside prestigious technical roles within leading PSUs.

This repository serves as a centralized documentation hub compiled from authoritative open-source archives, topper strategies, and verified learning pathways for your GATE CSE study material search.

1. Core Syllabus Structure & Weightage Analysis

Stop chasing Windows 11 alternatives or experimenting with risky third-party builds to upgrade from Windows 10 or trying to debloat mainstream editions. The ideal solution is already available: Windows 11 IoT LTSC.

It's a lightweight, stable, and bloat-free edition of Windows 11 that's perfect for productivity, development, or even gaming without the unnecessary apps, ads, or forced updates found in mainstream editions. Best of all, if your PC runs Windows 10 well, it'll handle Windows 11 IoT LTSC just as smoothly, with no performance drop or compatibility issues.

In this guide, I'll walk you through everything you need to know about Windows 11 IoT LTSC: how to prepare your system, install the OS, and configure it for daily use. By the end, you'll have a streamlined Windows setup perfect for productivity, development, or even gaming without the baggage of mainstream editions.

At the time of writing, the latest releas

This is a collection of free e-books about Artificial Intelligence(Machine Learning, Planning) and Data Science etc. .

ML, ebook, ebooks, books, book, machine learning, statistics, free

Handbook of Bayesian Deep Learning

For Apple Silicon Macs (M1–M5). Free. No CrossOver license needed.

EU5 has no Mac version, and the popular CrossOver/Wine recipes broke with patch 1.3 "Pavia" (the game hangs or silently dies). This guide gets EU5 1.3 running natively-fast on your Mac — including the 3D terrain, which even working setups usually have disabled — and with a fully working, visible Steam client (no black window, no engine-swapping).

It was worked out on an M5 Max running macOS 26, and every step below was validated on

[الدور والمسؤولية] أنت الآن تعمل بصفة Staff Software Engineer ومدير تقني Tech Lead. مهمتك التخطيط المعماري الصارم للمشروع التالي: [أدخل وصف المشروع هنا]

[قواعد ما قبل التتخطيط] قبل البدء بالبروتوكولات، يجب أن تطبق مبدأ "Think Before Coding":

See the following links for further updates to Github Desktop for Ubuntu. These are official instructions. (also mentioned by fetwar on Nov 3, 2023)

• How to Install
• Latest Releases

For the sake of "maintaining the tradition" here is the updated version.

A field-by-field reference for the CapCut / JianYing project format — what's in materials, what's in tracks, which version added which field, and the jq one-liners that pull data out cleanly.

Last tested: May 2026 (capcut-cli v0.5.0; CapCut 6.x–9.x, JianYing 5.9.0). See Changelog at the bottom.

If this saves you a reverse-engineering session, follow @renezander030 — more notes on the CapCut / JianYing draft format and the CLI that edits it.

Source for every field below: github.com/renezander030/capcut-cli — docs/draft-schema/ (~3,700 lines), distilled here.

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.

Markdown - это облегчённый язык разметки, который преобразует текст в структурированный HTML. Следующее руководство поможет вам разобраться, как использовать Markdown.

# Заголовок первого уровня
## Заголовок второго уровня
### Заголовок третьего уровня
#### Заголовок четвёртого уровня
##### Заголовок пятого уровня