🚀 Master Data Science & Programming!
Unlock your potential with this curated list of Telegram channels. Whether you need books, datasets, interview prep, or project ideas, we have the perfect resource for you. Join the community today!
🔰 Machine Learning with Python
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
https://news.1rj.ru/str/CodeProgrammer
🔖 Machine Learning
Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.
https://news.1rj.ru/str/DataScienceM
🧠 Code With Python
This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA – perfect for learning, coding, and mastering key programming skills.
https://news.1rj.ru/str/DataScience4
🎯 PyData Careers | Quiz
Python Data Science jobs, interview tips, and career insights for aspiring professionals.
https://news.1rj.ru/str/DataScienceQ
💾 Kaggle Data Hub
Your go-to hub for Kaggle datasets – explore, analyze, and leverage data for Machine Learning and Data Science projects.
https://news.1rj.ru/str/datasets1
🧑🎓 Udemy Coupons | Courses
The first channel in Telegram that offers free Udemy coupons
https://news.1rj.ru/str/DataScienceC
😀 ML Research Hub
Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.
https://news.1rj.ru/str/DataScienceT
💬 Data Science Chat
An active community group for discussing data challenges and networking with peers.
https://news.1rj.ru/str/DataScience9
🐍 Python Arab| بايثون عربي
The largest Arabic-speaking group for Python developers to share knowledge and help.
https://news.1rj.ru/str/PythonArab
🖊 Data Science Jupyter Notebooks
Explore the world of Data Science through Jupyter Notebooks—insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
https://news.1rj.ru/str/DataScienceN
📺 Free Online Courses | Videos
Free online courses covering data science, machine learning, analytics, programming, and essential skills for learners.
https://news.1rj.ru/str/DataScienceV
📈 Data Analytics
Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making.
https://news.1rj.ru/str/DataAnalyticsX
🎧 Learn Python Hub
Master Python with step-by-step courses – from basics to advanced projects and practical applications.
https://news.1rj.ru/str/Python53
⭐️ Research Papers
Professional Academic Writing & Simulation Services
https://news.1rj.ru/str/DataScienceY
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Admin: @HusseinSheikho
Unlock your potential with this curated list of Telegram channels. Whether you need books, datasets, interview prep, or project ideas, we have the perfect resource for you. Join the community today!
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
https://news.1rj.ru/str/CodeProgrammer
Machine learning insights, practical tutorials, and clear explanations for beginners and aspiring data scientists. Follow the channel for models, algorithms, coding guides, and real-world ML applications.
https://news.1rj.ru/str/DataScienceM
This channel delivers clear, practical content for developers, covering Python, Django, Data Structures, Algorithms, and DSA – perfect for learning, coding, and mastering key programming skills.
https://news.1rj.ru/str/DataScience4
Python Data Science jobs, interview tips, and career insights for aspiring professionals.
https://news.1rj.ru/str/DataScienceQ
Your go-to hub for Kaggle datasets – explore, analyze, and leverage data for Machine Learning and Data Science projects.
https://news.1rj.ru/str/datasets1
The first channel in Telegram that offers free Udemy coupons
https://news.1rj.ru/str/DataScienceC
Advancing research in Machine Learning – practical insights, tools, and techniques for researchers.
https://news.1rj.ru/str/DataScienceT
An active community group for discussing data challenges and networking with peers.
https://news.1rj.ru/str/DataScience9
The largest Arabic-speaking group for Python developers to share knowledge and help.
https://news.1rj.ru/str/PythonArab
Explore the world of Data Science through Jupyter Notebooks—insights, tutorials, and tools to boost your data journey. Code, analyze, and visualize smarter with every post.
https://news.1rj.ru/str/DataScienceN
Free online courses covering data science, machine learning, analytics, programming, and essential skills for learners.
https://news.1rj.ru/str/DataScienceV
Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making.
https://news.1rj.ru/str/DataAnalyticsX
Master Python with step-by-step courses – from basics to advanced projects and practical applications.
https://news.1rj.ru/str/Python53
Professional Academic Writing & Simulation Services
https://news.1rj.ru/str/DataScienceY
━━━━━━━━━━━━━━━━━━
Admin: @HusseinSheikho
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📌 How to Facilitate Effective AI Programming
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-29 | ⏱️ Read time: 7 min read
How to ensure your coding agent has the same context as you
#DataScience #AI #Python
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-29 | ⏱️ Read time: 7 min read
How to ensure your coding agent has the same context as you
#DataScience #AI #Python
📌 Machine Learning vs AI Engineer: What Are the Differences?
🗂 Category: CAREER ADVICE
🕒 Date: 2025-12-29 | ⏱️ Read time: 7 min read
One of the most confusing questions in tech right now is: What is the difference…
#DataScience #AI #Python
🗂 Category: CAREER ADVICE
🕒 Date: 2025-12-29 | ⏱️ Read time: 7 min read
One of the most confusing questions in tech right now is: What is the difference…
#DataScience #AI #Python
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📌 Implementing Vibe Proving with Reinforcement Learning
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-29 | ⏱️ Read time: 9 min read
How to make LLMs reason with verifiable, step-by-step logic (Part 2)
#DataScience #AI #Python
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-29 | ⏱️ Read time: 9 min read
How to make LLMs reason with verifiable, step-by-step logic (Part 2)
#DataScience #AI #Python
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📌 Overcoming Nonsmoothness and Control Chattering in Nonconvex Optimal Control Problems
🗂 Category: ROBOTICS
🕒 Date: 2025-12-30 | ⏱️ Read time: 17 min read
With some hints for good numerics
#DataScience #AI #Python
🗂 Category: ROBOTICS
🕒 Date: 2025-12-30 | ⏱️ Read time: 17 min read
With some hints for good numerics
#DataScience #AI #Python
📌 The Machine Learning “Advent Calendar” Bonus 1: AUC in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-30 | ⏱️ Read time: 8 min read
AUC measures how well a model ranks positives above negatives, independent of any chosen threshold.
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-30 | ⏱️ Read time: 8 min read
AUC measures how well a model ranks positives above negatives, independent of any chosen threshold.
#DataScience #AI #Python
Forwarded from Machine Learning with Python
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📌 Agents Under the Curve (AUC)
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-30 | ⏱️ Read time: 15 min read
Towards understanding if your agentic solution is actually better
#DataScience #AI #Python
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-30 | ⏱️ Read time: 15 min read
Towards understanding if your agentic solution is actually better
#DataScience #AI #Python
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📌 Production-Ready LLMs Made Simple with the NeMo Agent Toolkit
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-31 | ⏱️ Read time: 23 min read
From simple chat to multi-agent reasoning and real-time REST APIs
#DataScience #AI #Python
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-31 | ⏱️ Read time: 23 min read
From simple chat to multi-agent reasoning and real-time REST APIs
#DataScience #AI #Python
📌 What Advent of Code Has Taught Me About Data Science
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-31 | ⏱️ Read time: 10 min read
Five key learnings that I discovered during a programming challenge and how they apply to…
#DataScience #AI #Python
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-31 | ⏱️ Read time: 10 min read
Five key learnings that I discovered during a programming challenge and how they apply to…
#DataScience #AI #Python
📌 Chunk Size as an Experimental Variable in RAG Systems
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-31 | ⏱️ Read time: 12 min read
Understanding retrieval in RAG systems by experimenting with different chunk sizes
#DataScience #AI #Python
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-31 | ⏱️ Read time: 12 min read
Understanding retrieval in RAG systems by experimenting with different chunk sizes
#DataScience #AI #Python
📌 The Machine Learning “Advent Calendar” Bonus 2: Gradient Descent Variants in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-31 | ⏱️ Read time: 8 min read
Gradient Descent, Momentum, RMSProp, and Adam all aim for the same minimum. They do not…
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-31 | ⏱️ Read time: 8 min read
Gradient Descent, Momentum, RMSProp, and Adam all aim for the same minimum. They do not…
#DataScience #AI #Python
amazing bot to get all resources about any things search it on telegram
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📌 EDA in Public (Part 3): RFM Analysis for Customer Segmentation in Pandas
🗂 Category: DATA SCIENCE
🕒 Date: 2026-01-01 | ⏱️ Read time: 13 min read
How to build, score, and interpret RFM segments step by step
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2026-01-01 | ⏱️ Read time: 13 min read
How to build, score, and interpret RFM segments step by step
#DataScience #AI #Python
Forwarded from Machine Learning with Python
Harvard has made its textbook on ML systems publicly available. It's extremely practical: not just about how to train models, but how to build production systems around them - what really matters.
The topics there are really top-notch:
> Building autograd, optimizers, attention, and mini-PyTorch from scratch to understand how the framework is structured internally. (This is really awesome)
> Basic things about DL: batches, computational accuracy, model architectures, and training
> Optimizing ML performance, hardware acceleration, benchmarking, and efficiency
So this isn't just an introductory course on ML, but a complete cycle from start to practical application. You can already read the book and view the code for free. For 2025, this is one of the strongest textbooks to have been released, so it's best not to miss out.
The repository is here, with a link to the book inside👏
👉 @codeprogrammer
The topics there are really top-notch:
> Building autograd, optimizers, attention, and mini-PyTorch from scratch to understand how the framework is structured internally. (This is really awesome)
> Basic things about DL: batches, computational accuracy, model architectures, and training
> Optimizing ML performance, hardware acceleration, benchmarking, and efficiency
So this isn't just an introductory course on ML, but a complete cycle from start to practical application. You can already read the book and view the code for free. For 2025, this is one of the strongest textbooks to have been released, so it's best not to miss out.
The repository is here, with a link to the book inside
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📌 Deep Reinforcement Learning: The Actor-Critic Method
🗂 Category: REINFORCEMENT LEARNING
🕒 Date: 2026-01-01 | ⏱️ Read time: 19 min read
Robot friends collaborate to learn to fly a drone
#DataScience #AI #Python
🗂 Category: REINFORCEMENT LEARNING
🕒 Date: 2026-01-01 | ⏱️ Read time: 19 min read
Robot friends collaborate to learn to fly a drone
#DataScience #AI #Python
Cheat sheet for Python for Data Science: covers basic Python syntax (variables, data types, operations, strings), working with lists, NumPy arrays, indexing and slicing, main methods and functions, as well as importing libraries for data analysis
https://news.1rj.ru/str/DataScienceM
https://news.1rj.ru/str/DataScienceM
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📌 Drift Detection in Robust Machine Learning Systems
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-01-02 | ⏱️ Read time: 18 min read
A prerequisite for long-term success of machine learning systems
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2026-01-02 | ⏱️ Read time: 18 min read
A prerequisite for long-term success of machine learning systems
#DataScience #AI #Python
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📌 Off-Beat Careers That Are the Future Of Data
🗂 Category: DATA SCIENCE
🕒 Date: 2026-01-02 | ⏱️ Read time: 8 min read
The unconventional career paths you need to explore
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2026-01-02 | ⏱️ Read time: 8 min read
The unconventional career paths you need to explore
#DataScience #AI #Python
📌 The Real Challenge in Data Storytelling: Getting Buy-In for Simplicity
🗂 Category: DATA SCIENCE
🕒 Date: 2026-01-02 | ⏱️ Read time: 7 min read
What happens when your clear dashboard meets stakeholders who want everything on one screen
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2026-01-02 | ⏱️ Read time: 7 min read
What happens when your clear dashboard meets stakeholders who want everything on one screen
#DataScience #AI #Python
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Forwarded from Machine Learning with Python
All assignments for the #Stanford The Modern Software Developer course are now available online.
This is the first full-fledged university course that covers how code-generative #LLMs are changing every stage of the development lifecycle. The assignments are designed to take you from a beginner to a confident expert in using AI to boost productivity in development.
Enjoy your studies! ✌️
https://github.com/mihail911/modern-software-dev-assignments
https://news.1rj.ru/str/CodeProgrammer
This is the first full-fledged university course that covers how code-generative #LLMs are changing every stage of the development lifecycle. The assignments are designed to take you from a beginner to a confident expert in using AI to boost productivity in development.
Enjoy your studies! ✌️
https://github.com/mihail911/modern-software-dev-assignments
https://news.1rj.ru/str/CodeProgrammer
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