Github Top Repositories

🔥 Trending Repository: zvec 📝 Description: A lightweight, lightning-fast, in-process vector database 🔗 Repository URL: https://github.com/alibaba/zvec 🌐 Website: https://zvec.org/en/ 📖 Readme: https://github.com/alibaba/zvec#readme 📊 Statistics: 🌟 Stars: 967 stars 👀 Watchers: 4 🍴 Forks: 56 forks 💻 Programming Languages: C++ - SWIG - Python - C - CMake - ANTLR 🏷️ Related Topics:

#embedded_database #rag #vector_search #ann_search #vectordb

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SQL 𝗢𝗿𝗱𝗲𝗿 𝗢𝗳 𝗘𝘅𝗲𝗰𝘂𝘁𝗶𝗼𝗻 1 → FROM (Tables selected). 2 → WHERE (Filters applied). 3 → GROUP BY (Rows grouped). 4 → HAVING (Filter on grouped data). 5 → SELECT (Columns selected). 6 → ORDER BY (Sort the data). 7 → LIMIT (Restrict number of rows). 𝗖𝗼𝗺𝗺𝗼𝗻 𝗤𝘂𝗲𝗿𝗶𝗲𝘀 𝗧𝗼 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 ↓ ↬ Find the second-highest salary: SELECT MAX(Salary) FROM Employees WHERE Salary < (SELECT MAX(Salary) FROM Employees); ↬ Find duplicate records: SELECT Name, COUNT(*) FROM Emp GROUP BY Name HAVING COUNT(*) > 1;

🔥 Trending Repository: DebugSwift 📝 Description: A toolkit to make debugging iOS applications easier 🚀 🔗 Repository URL: https://github.com/DebugSwift/DebugSwift 📖 Readme: https://github.com/DebugSwift/DebugSwift#readme 📊 Statistics: 🌟 Stars: 1.3K stars 👀 Watchers: 7 🍴 Forks: 118 forks 💻 Programming Languages: Swift 🏷️ Related Topics:

#debugger #swift #debugging #ui #networking #log #analytics #analysis #view #cocoapods #sandbox #uikit #debug #performance_analysis #crashlytics #hacktoberfest #leak_detection #logs_analysis #layout_debugger #swift6

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🔥 Trending Repository: slime 📝 Description: slime is an LLM post-training framework for RL Scaling. 🔗 Repository URL: https://github.com/THUDM/slime 🌐 Website: https://thudm.github.io/slime 📖 Readme: https://github.com/THUDM/slime#readme 📊 Statistics: 🌟 Stars: 4K stars 👀 Watchers: 16 🍴 Forks: 523 forks 💻 Programming Languages: Python - Shell 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

🔥 Trending Repository: superhuman 📝 Description: No description available 🔗 Repository URL: https://github.com/google-deepmind/superhuman 📖 Readme: https://github.com/google-deepmind/superhuman#readme 📊 Statistics: 🌟 Stars: 268 stars 👀 Watchers: 14 🍴 Forks: 21 forks 💻 Programming Languages: TeX 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

🔥 Trending Repository: MTProxy 📝 Description: No description available 🔗 Repository URL: https://github.com/TelegramMessenger/MTProxy 📖 Readme: https://github.com/TelegramMessenger/MTProxy#readme 📊 Statistics: 🌟 Stars: 5.8K stars 👀 Watchers: 233 🍴 Forks: 994 forks 💻 Programming Languages: C - Makefile 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

🔥 Trending Repository: aios-core 📝 Description: Synkra AIOS: AI-Orchestrated System for Full Stack Development - Core Framework v4.0 🔗 Repository URL: https://github.com/SynkraAI/aios-core 🌐 Website: https://github.com/allfluence/aios-core 📖 Readme: https://github.com/SynkraAI/aios-core#readme 📊 Statistics: 🌟 Stars: 291 stars 👀 Watchers: 29 🍴 Forks: 171 forks 💻 Programming Languages: JavaScript - Python - Shell - Handlebars - PLpgSQL - CSS 🏷️ Related Topics:

#nodejs #cli #development #automation #framework #typescript #ai #orchestration #fullstack #agents #ai_agents #claude

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Alpha $SOL Team launching today at 20:00 UTC, make sure you’re not fading! Their last 3 launches: 156x , 35x , 23x Massive marketing push is lined up right after launch and I’m personally buying 3k DEX boosts to send this🚀 Make sure you join the channel to not miss the launch at 20:00 UTC 👇👇👇👇👇👇👇👇👇👇 https://t.me/+WvuT-nmk3PcwZmNk https://t.me/+WvuT-nmk3PcwZmNk #ad InsideAds

200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we completed in 6 days, let’s do this one even quicker! Join my free group Before closing 👇 https://t.me/+DAKLP7eUy9Y3ZjY0 #ad InsideAds

🔥 Trending Repository: cinny 📝 Description: Yet another matrix client 🔗 Repository URL: https://github.com/cinnyapp/cinny 🌐 Website: https://cinny.in 📖 Readme: https://github.com/cinnyapp/cinny#readme 📊 Statistics: 🌟 Stars: 2.8K stars 👀 Watchers: 19 🍴 Forks: 385 forks 💻 Programming Languages: TypeScript 🏷️ Related Topics:

#client #reactjs #matrix #hacktoberfest #matrix_client #matrix_org #cinny #cinnyapp

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🔥 Trending Repository: rowboat 📝 Description: Open-source AI coworker, with memory 🔗 Repository URL: https://github.com/rowboatlabs/rowboat 🌐 Website: https://www.rowboatlabs.com 📖 Readme: https://github.com/rowboatlabs/rowboat#readme 📊 Statistics: 🌟 Stars: 4.9K stars 👀 Watchers: 38 🍴 Forks: 388 forks 💻 Programming Languages: TypeScript - CSS - MDX - Python - JavaScript - Dockerfile 🏷️ Related Topics:

#productivity #open_source #ai #orchestration #multiagent #agents #ai_agents #llm #generative_ai #chatgpt #opeani #ai_agents_automation #claude_code #agents_sdk #claude_cowork

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🔥 Trending Repository: Personal_AI_Infrastructure 📝 Description: Agentic AI Infrastructure for magnifying HUMAN capabilities. 🔗 Repository URL: https://github.com/danielmiessler/Personal_AI_Infrastructure 📖 Readme: https://github.com/danielmiessler/Personal_AI_Infrastructure#readme 📊 Statistics: 🌟 Stars: 7.2K stars 👀 Watchers: 120 🍴 Forks: 1.1K forks 💻 Programming Languages: TypeScript - Vue - Python - Shell - CSS - Handlebars 🏷️ Related Topics:

#productivity #ai #humans #augmentation

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🔹 DATA SCIENCE – INTERVIEW REVISION SHEET* *1️⃣ What is Data Science?* > “Data science is the process of using data, statistics, and machine learning to extract insights and build predictive or decision-making models.” Difference from Data Analytics: - Data Analytics → past & present (what/why) - Data Science → future & automation (what will happen) *2️⃣ Data Science Lifecycle (Very Important)* 1. Business problem understanding 2. Data collection 3. Data cleaning & preprocessing 4. Exploratory Data Analysis (EDA) 5. Feature engineering 6. Model building 7. Model evaluation 8. Deployment & monitoring Interview line: > “I always start from business understanding, not the model.” *3️⃣ Data Types* - Structured → tables, SQL - Semi-structured → JSON, logs - Unstructured → text, images *4️⃣ Statistics You MUST Know* - Central tendency: Mean, Median (use when outliers exist) - Spread: Variance, Standard deviation - Correlation ≠ causation - Normal distribution - Skewness (income → right skewed) *5️⃣ Data Cleaning & Preprocessing* Steps you should say in interviews: 1. Handle missing values 2. Remove duplicates 3. Treat outliers 4. Encode categorical variables 5. Scale numerical data Scaling: - Min-Max → bounded range - Standardization → normal distribution *6️⃣ Feature Engineering (Interview Favorite)* > “Feature engineering is creating meaningful input variables that improve model performance.” Examples: - Extract month from date - Create customer lifetime value - Binning age groups *7️⃣ Machine Learning Basics* - Supervised learning: Regression, Classification - Unsupervised learning: Clustering, Dimensionality reduction *8️⃣ Common Algorithms (Know WHEN to use)* - Regression: Linear regression → continuous output - Classification: Logistic regression, Decision tree, Random forest, SVM - Unsupervised: K-Means → segmentation, PCA → dimensionality reduction *9️⃣ Overfitting vs Underfitting* - Overfitting → model memorizes training data - Underfitting → model too simple Fixes: - Regularization - More data - Cross-validation *🔟 Model Evaluation Metrics* - Classification: Accuracy, Precision, Recall, F1 score, ROC-AUC - Regression: MAE, RMSE Interview line: > “Metric selection depends on business problem.” *1️⃣1️⃣ Imbalanced Data Techniques* - Class weighting - Oversampling / undersampling - SMOTE - Metric preference: Precision, Recall, F1, ROC-AUC *1️⃣2️⃣ Python for Data Science* Core libraries: - NumPy - Pandas - Matplotlib / Seaborn - Scikit-learn Must know: - loc vs iloc - Groupby - Vectorization *1️⃣3️⃣ Model Deployment (Basic Understanding)* - Batch prediction - Real-time prediction - Model monitoring - Model drift Interview line: > “Models must be monitored because data changes over time.” *1️⃣4️⃣ Explain Your Project (Template)* > “The goal was _. I cleaned the data using _. I performed EDA to identify _. I built _ model and evaluated using _. The final outcome was _.” *1️⃣5️⃣ HR-Style Data Science Answers* Why data science? > “I enjoy solving complex problems using data and building models that automate decisions.” Biggest challenge: “Handling messy real-world data.” Strength: “Strong foundation in statistics and ML.” *🔥 LAST-DAY INTERVIEW TIPS* - Explain intuition, not math - Don’t jump to algorithms immediately - Always connect model → business value - Say assumptions clearly

200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we completed in 6 days, let’s do this one even quicker! Join my free group Before closing 👇 https://t.me/+DAKLP7eUy9Y3ZjY0 #ad InsideAds

🔥 Trending Repository: claude-skills 📝 Description: 65 Specialized Skills for Full-Stack Developers. Transform Claude Code into your expert pair programmer. 🔗 Repository URL: https://github.com/Jeffallan/claude-skills 📖 Readme: https://github.com/Jeffallan/claude-skills#readme 📊 Statistics: 🌟 Stars: 498 stars 👀 Watchers: 6 🍴 Forks: 56 forks 💻 Programming Languages: Python - JavaScript - HTML - Astro - Shell - Makefile 🏷️ Related Topics:

#ai_agents #claude #claude_code #claude_skills #claude_marketplace

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🔥 Trending Repository: free-llm-api-resources 📝 Description: A list of free LLM inference resources accessible via API. 🔗 Repository URL: https://github.com/cheahjs/free-llm-api-resources 📖 Readme: https://github.com/cheahjs/free-llm-api-resources#readme 📊 Statistics: 🌟 Stars: 8.5K stars 👀 Watchers: 138 🍴 Forks: 840 forks 💻 Programming Languages: Python 🏷️ Related Topics:

#ai #gemini #openai #llama #claude #llm

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🔥 Trending Repository: claude-code-pm-course 📝 Description: Interactive course teaching Product Managers how to use Claude Code effectively 🔗 Repository URL: https://github.com/carlvellotti/claude-code-pm-course 🌐 Website: https://claude-code-pm-course.vercel.app 📖 Readme: https://github.com/carlvellotti/claude-code-pm-course#readme 📊 Statistics: 🌟 Stars: 669 stars 👀 Watchers: 11 🍴 Forks: 139 forks 💻 Programming Languages: MDX - HTML - Python - JavaScript - Shell - TypeScript - CSS 🏷️ Related Topics: Not available ================================== 🧠 By: https://t.me/DataScienceM

200$ to 20k$ SOL Challenge! As promised, i will do another challenge for those who missed the previous one! Last one we completed in 6 days, let’s do this one even quicker! Join my free group Before closing 👇 https://t.me/+DAKLP7eUy9Y3ZjY0 #ad InsideAds

🔥 Trending Repository: gh-aw 📝 Description: GitHub Agentic Workflows 🔗 Repository URL: https://github.com/github/gh-aw 🌐 Website: https://gh.io/gh-aw 📖 Readme: https://github.com/github/gh-aw#readme 📊 Statistics: 🌟 Stars: 609 stars 👀 Watchers: 4 🍴 Forks: 65 forks 💻 Programming Languages: Go - JavaScript - Shell 🏷️ Related Topics:

#ci #actions #copilot #codex #cai #github_actions #gh_extension #claude_code

================================== 🧠 By: https://t.me/DataScienceM