🔥 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

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 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

==================================
🧠 By: https://t.iss.one/DataScienceM

🔹 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

🔥 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

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 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

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 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

==================================
🧠 By: https://t.iss.one/DataScienceM

The biggest surprise for our valued audience: we are offering 40 paid courses completely free.

Enroll Here and request
https://adsly.me/l/jwxfnss0yi

We use a spam/flood protection system to ensure that all registered users are real people.

🔥 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

==================================
🧠 By: https://t.iss.one/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.iss.one/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.iss.one/DataScienceM

🔥 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.iss.one/DataScienceM

🔥 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

==================================
🧠 By: https://t.iss.one/DataScienceM

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;


https://t.iss.one/DataScienceM

🔥 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

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 Trending Repository: wifi-densepose

📝 Description: Production-ready implementation of InvisPose - a revolutionary WiFi-based dense human pose estimation system that enables real-time full-body tracking through walls using commodity mesh routers

🔗 Repository URL: https://github.com/ruvnet/wifi-densepose

📖 Readme: https://github.com/ruvnet/wifi-densepose#readme

📊 Statistics:
🌟 Stars: 6K stars
👀 Watchers: 39
🍴 Forks: 544 forks

💻 Programming Languages: Python - Rust - JavaScript - Shell - HTML - CSS

🏷️ Related Topics: Not available

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 Trending Repository: unstract

📝 Description: No-code LLM Platform to launch APIs and ETL Pipelines to structure unstructured documents

🔗 Repository URL: https://github.com/Zipstack/unstract

🌐 Website: https://unstract.com

📖 Readme: https://github.com/Zipstack/unstract#readme

📊 Statistics:
🌟 Stars: 6.2K stars
👀 Watchers: 46
🍴 Forks: 588 forks

💻 Programming Languages: Python - JavaScript - Shell - CSS

🏷️ Related Topics:

#unstructured_data #etl_pipeline #llm_platform

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 Trending Repository: letta-code

📝 Description: The memory-first coding agent

🔗 Repository URL: https://github.com/letta-ai/letta-code

🌐 Website: https://docs.letta.com/letta-code

📖 Readme: https://github.com/letta-ai/letta-code#readme

📊 Statistics:
🌟 Stars: 1.1K stars
👀 Watchers: 7
🍴 Forks: 133 forks

💻 Programming Languages: TypeScript

🏷️ Related Topics: Not available

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 Trending Repository: ruby

📝 Description: The Ruby Programming Language

🔗 Repository URL: https://github.com/ruby/ruby

🌐 Website: https://www.ruby-lang.org/

📖 Readme: https://github.com/ruby/ruby#readme

📊 Statistics:
🌟 Stars: 23.3K stars
👀 Watchers: 1.1k
🍴 Forks: 5.6K forks

💻 Programming Languages: Ruby - C - Rust - C++ - Yacc - HTML

🏷️ Related Topics:

#ruby #c #language #programming_language #rust #jit #object_oriented #ruby_language

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 Trending Repository: gogcli

📝 Description: Google Suite CLI: Gmail, GCal, GDrive, GContacts.

🔗 Repository URL: https://github.com/steipete/gogcli

🌐 Website: https://gogcli.sh

📖 Readme: https://github.com/steipete/gogcli#readme

📊 Statistics:
🌟 Stars: 2.7K stars
👀 Watchers: 19
🍴 Forks: 242 forks

💻 Programming Languages: Go - HTML - Shell

🏷️ Related Topics:

#google #gmail #gdrive #gcal #gcontacts

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 Trending Repository: moonshine

📝 Description: Fast and accurate automatic speech recognition (ASR) for edge devices

🔗 Repository URL: https://github.com/moonshine-ai/moonshine

📖 Readme: https://github.com/moonshine-ai/moonshine#readme

📊 Statistics:
🌟 Stars: 3.6K stars
👀 Watchers: 43
🍴 Forks: 175 forks

💻 Programming Languages: C - C++ - Python - Swift - Java - Jupyter Notebook

🏷️ Related Topics: Not available

==================================
🧠 By: https://t.iss.one/DataScienceM

🔥 Trending Repository: brave-browser

📝 Description: Brave browser for Android, iOS, Linux, macOS, Windows.

🔗 Repository URL: https://github.com/brave/brave-browser

🌐 Website: https://brave.com

📖 Readme: https://github.com/brave/brave-browser#readme

📊 Statistics:
🌟 Stars: 21.5K stars
👀 Watchers: 388
🍴 Forks: 3K forks

💻 Programming Languages: Not available

🏷️ Related Topics:

#windows #macos #linux #browser #chromium #brave

==================================
🧠 By: https://t.iss.one/DataScienceM