Data Science Machine Learning Data Analysis
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This channel is for Programmers, Coders, Software Engineers.

1- Data Science
2- Machine Learning
3- Data Visualization
4- Artificial Intelligence
5- Data Analysis
6- Statistics
7- Deep Learning

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πŸ”₯ Trending Repository: abogen

πŸ“ Description: Generate audiobooks from EPUBs, PDFs and text with synchronized captions.

πŸ”— Repository URL: https://github.com/denizsafak/abogen

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

πŸ“– Readme: https://github.com/denizsafak/abogen#readme

πŸ“Š Statistics:
🌟 Stars: 3.1K stars
πŸ‘€ Watchers: 18
🍴 Forks: 159 forks

πŸ’» 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


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🧠 By: https://t.iss.one/DataScienceM
πŸ”₯ Trending Repository: ML-From-Scratch

πŸ“ 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.

πŸ”— Repository URL: https://github.com/eriklindernoren/ML-From-Scratch

πŸ“– Readme: https://github.com/eriklindernoren/ML-From-Scratch#readme

πŸ“Š Statistics:
🌟 Stars: 27.8K stars
πŸ‘€ Watchers: 951
🍴 Forks: 4.8K forks

πŸ’» Programming Languages: Python

🏷️ Related Topics:
#data_science #machine_learning #data_mining #deep_learning #genetic_algorithm #deep_reinforcement_learning #machine_learning_from_scratch


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🧠 By: https://t.iss.one/DataScienceM
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πŸ“Œ How to Context Engineer to Optimize Question Answering Pipelines

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2025-09-05 | ⏱️ Read time: 9 min read

Learn how to apply context engineering to enhance your question answering systems.
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πŸ“Œ Showcasing Your Work on HuggingFace Spaces

πŸ—‚ Category: PRODUCTIVITY

πŸ•’ Date: 2025-09-05 | ⏱️ Read time: 9 min read

Building an app is exciting – but sharing it is where the real value kicks…
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πŸ“Œ AI Operations Under the Hood: Challenges and Best Practices

πŸ—‚ Category: LLM APPLICATIONS

πŸ•’ Date: 2025-09-05 | ⏱️ Read time: 18 min read

Building robust, reproducible, and reliable GenAI applications requires a framework of continuous improvement, rigorous evaluation,…
πŸ“Œ Zero-Inflated Data: A Comparison of Regression Models

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2025-09-05 | ⏱️ Read time: 13 min read

How to detect it and which model to choose.
πŸ“Œ Tool Masking: The Layer MCP Forgot

πŸ—‚ Category: AGENTIC AI

πŸ•’ Date: 2025-09-05 | ⏱️ Read time: 16 min read

Tool masking for AI improves AI agents: shape MCP tool surfaces to cut tokens and…
πŸ“Œ Should We Use LLMs As If They Were Swiss Knives?

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ Date: 2025-09-04 | ⏱️ Read time: 9 min read

A logic game performance comparison between popular LLMs and a custom-made algorithm
πŸ“Œ A Visual Guide to Tuning Random Forest Hyperparameters

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2025-09-04 | ⏱️ Read time: 8 min read

How hyperparameter tuning visually changes random forests
πŸ“Œ MobileNetV1 Paper Walkthrough: The Tiny Giant

πŸ—‚ Category: DEEP LEARNING

πŸ•’ Date: 2025-09-04 | ⏱️ Read time: 26 min read

Understanding and implementing MobileNetV1 from scratch with PyTorch
πŸ“Œ Using LangGraph and MCP Servers to Create My Own Voice Assistant

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ Date: 2025-09-04 | ⏱️ Read time: 30 min read

Built over 14 days, all locally run, no API keys, cloud services, or subscription fees.
πŸ“Œ Boosting Your Anomaly Detection With LLMs

πŸ—‚ Category: LARGE LANGUAGE MODELS

πŸ•’ Date: 2025-09-04 | ⏱️ Read time: 17 min read

The 7 emerging application patterns you should know
πŸ“Œ The Programming Skills You Need for Today’s Data Roles

πŸ—‚ Category: THE VARIABLE

πŸ•’ Date: 2025-09-04 | ⏱️ Read time: 3 min read

How to stand out in a crowded field
πŸ“Œ Useful Python Libraries You Might Not Have Heard Of:β€Šβ€ŠFreezegun

πŸ—‚ Category: PROGRAMMING

πŸ•’ Date: 2025-09-03 | ⏱️ Read time: 12 min read

Bring time to a standstill in your Python tests
πŸ“Œ AI FOMO, Shadow AI, and Other Business Problems

πŸ—‚ Category: ARTIFICIAL INTELLIGENCE

πŸ•’ 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…
πŸ“Œ Hands On Time Series Modeling of Rare Events, with Python

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2025-09-03 | ⏱️ Read time: 11 min read

This is how to model rare events occurrences in a time series in a few…
πŸ“Œ Stochastic Differential Equations and Temperature β€” NASA Climate Data pt. 2

πŸ—‚ Category: MATH

πŸ•’ Date: 2025-09-03 | ⏱️ Read time: 14 min read

The Ornstein-Uhlenbeck process in Python
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πŸ“Œ What Being a Data Scientist at a Startup Really Looks Like

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2025-09-03 | ⏱️ Read time: 9 min read

What I learned about growth, visibility, and chaos over the past five years
πŸ“Œ A Deep Dive into RabbitMQ & Python’s Celery: How to Optimise Your Queues

πŸ—‚ Category: PROGRAMMING

πŸ•’ Date: 2025-09-02 | ⏱️ Read time: 12 min read

Key lessons I’ve learned running RabbitMQ + Celery in production
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πŸ“Œ Implementing the Caesar Cipher in Python

πŸ—‚ Category: PROGRAMMING

πŸ•’ Date: 2025-09-02 | ⏱️ Read time: 7 min read

Julius Caesar was a Roman ruler known for his military strategies and excellent leadership. Named…
πŸ“Œ How to Scale Your AI Search to Handle 10M Queries with 5 Powerful Techniques

πŸ—‚ Category: CONVERSATIONAL AI

πŸ•’ Date: 2025-09-02 | ⏱️ Read time: 9 min read

Optimize your AI search with RAG, contextual retrieval and evaluations