🔥 Trending Repository: 500-AI-Agents-Projects

📝 Description: The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation, illustrating how AI agents are transforming sectors such as healthcare, finance, education, retail, and more.

🔗 Repository URL: https://github.com/ashishpatel26/500-AI-Agents-Projects

🌐 Website: https://github.com/ashishpatel26/500-AI-Agents-Projects

📖 Readme: https://github.com/ashishpatel26/500-AI-Agents-Projects#readme

📊 Statistics:
🌟 Stars: 7K stars
👀 Watchers: 105
🍴 Forks: 1.3K forks

💻 Programming Languages: Not available

🏷️ Related Topics:

#ai_agents #genai

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

🔥 Trending Repository: cognitive-load

📝 Description: 🧠 Cognitive Load is what matters

🔗 Repository URL: https://github.com/zakirullin/cognitive-load

📖 Readme: https://github.com/zakirullin/cognitive-load#readme

📊 Statistics:
🌟 Stars: 9.4K stars
👀 Watchers: 86
🍴 Forks: 200 forks

💻 Programming Languages: Not available

🏷️ Related Topics: Not available

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

🔥 Trending Repository: abogen

📝 Description: Generate audiobooks from EPUBs, PDFs and text with synchronized captions.

🔗 Repository URL: https://github.com/denizsafak/abogen

🌐 Website: https://pypi.org/project/abogen/

📖 Readme: https://github.com/denizsafak/abogen#readme

📊 Statistics:
🌟 Stars: 3.1K stars
👀 Watchers: 18
🍴 Forks: 159 forks

💻 Programming Languages: Python - Batchfile - Dockerfile

🏷️ Related Topics:

#text_to_speech #audiobook #tts #speech_synthesis #subtitles #audiobooks #narrator #content_creator #voice_synthesis #epub_converter #kokoro #content_creation #text_to_audio #media_generation #kokoro_tts #kokoro_82m

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

🔥 Trending Repository: ML-From-Scratch

📝 Description: Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

🔗 Repository URL: https://github.com/eriklindernoren/ML-From-Scratch

📖 Readme: https://github.com/eriklindernoren/ML-From-Scratch#readme

📊 Statistics:
🌟 Stars: 27.8K stars
👀 Watchers: 951
🍴 Forks: 4.8K forks

💻 Programming Languages: Python

🏷️ Related Topics:

#data_science #machine_learning #data_mining #deep_learning #genetic_algorithm #deep_reinforcement_learning #machine_learning_from_scratch

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

📌 How to Context Engineer to Optimize Question Answering Pipelines

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read

Learn how to apply context engineering to enhance your question answering systems.

📌 Showcasing Your Work on HuggingFace Spaces

🗂 Category: PRODUCTIVITY

🕒 Date: 2025-09-05 | ⏱️ Read time: 9 min read

Building an app is exciting – but sharing it is where the real value kicks…

📌 AI Operations Under the Hood: Challenges and Best Practices

🗂 Category: LLM APPLICATIONS

🕒 Date: 2025-09-05 | ⏱️ Read time: 18 min read

Building robust, reproducible, and reliable GenAI applications requires a framework of continuous improvement, rigorous evaluation,…

📌 Zero-Inflated Data: A Comparison of Regression Models

🗂 Category: DATA SCIENCE

🕒 Date: 2025-09-05 | ⏱️ Read time: 13 min read

How to detect it and which model to choose.

📌 Tool Masking: The Layer MCP Forgot

🗂 Category: AGENTIC AI

🕒 Date: 2025-09-05 | ⏱️ Read time: 16 min read

Tool masking for AI improves AI agents: shape MCP tool surfaces to cut tokens and…

📌 Should We Use LLMs As If They Were Swiss Knives?

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-09-04 | ⏱️ Read time: 9 min read

A logic game performance comparison between popular LLMs and a custom-made algorithm

📌 A Visual Guide to Tuning Random Forest Hyperparameters

🗂 Category: DATA SCIENCE

🕒 Date: 2025-09-04 | ⏱️ Read time: 8 min read

How hyperparameter tuning visually changes random forests

📌 MobileNetV1 Paper Walkthrough: The Tiny Giant

🗂 Category: DEEP LEARNING

🕒 Date: 2025-09-04 | ⏱️ Read time: 26 min read

Understanding and implementing MobileNetV1 from scratch with PyTorch

📌 Using LangGraph and MCP Servers to Create My Own Voice Assistant

🗂 Category: MACHINE LEARNING

🕒 Date: 2025-09-04 | ⏱️ Read time: 30 min read

Built over 14 days, all locally run, no API keys, cloud services, or subscription fees.

📌 Boosting Your Anomaly Detection With LLMs

🗂 Category: LARGE LANGUAGE MODELS

🕒 Date: 2025-09-04 | ⏱️ Read time: 17 min read

The 7 emerging application patterns you should know

📌 The Programming Skills You Need for Today’s Data Roles

🗂 Category: THE VARIABLE

🕒 Date: 2025-09-04 | ⏱️ Read time: 3 min read

How to stand out in a crowded field

📌 Useful Python Libraries You Might Not Have Heard Of:  Freezegun

🗂 Category: PROGRAMMING

🕒 Date: 2025-09-03 | ⏱️ Read time: 12 min read

Bring time to a standstill in your Python tests

📌 AI FOMO, Shadow AI, and Other Business Problems

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2025-09-03 | ⏱️ Read time: 6 min read

What’s the state of AI in business these days, and how much does it cost…

📌 Hands On Time Series Modeling of Rare Events, with Python

🗂 Category: DATA SCIENCE

🕒 Date: 2025-09-03 | ⏱️ Read time: 11 min read

This is how to model rare events occurrences in a time series in a few…

📌 Stochastic Differential Equations and Temperature — NASA Climate Data pt. 2

🗂 Category: MATH

🕒 Date: 2025-09-03 | ⏱️ Read time: 14 min read

The Ornstein-Uhlenbeck process in Python

📌 What Being a Data Scientist at a Startup Really Looks Like

🗂 Category: DATA SCIENCE

🕒 Date: 2025-09-03 | ⏱️ Read time: 9 min read

What I learned about growth, visibility, and chaos over the past five years