📌 The Subset Sum Problem Solved in Linear Time for Dense Enough Inputs
🗂 Category: ALGORITHMS
🕒 Date: 2025-12-18 | ⏱️ Read time: 31 min read
An optimal solution to the well-known NP-complete problem, when the input values are close enough…
#DataScience #AI #Python
🗂 Category: ALGORITHMS
🕒 Date: 2025-12-18 | ⏱️ Read time: 31 min read
An optimal solution to the well-known NP-complete problem, when the input values are close enough…
#DataScience #AI #Python
❤2
📌 Generating Artwork in Python Inspired by Hirst’s Million-Dollar Spots Painting
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-18 | ⏱️ Read time: 6 min read
Using Python to generate art
#DataScience #AI #Python
🗂 Category: PROGRAMMING
🕒 Date: 2025-12-18 | ⏱️ Read time: 6 min read
Using Python to generate art
#DataScience #AI #Python
❤2
📌 The Machine Learning “Advent Calendar” Day 18: Neural Network Classifier in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-18 | ⏱️ Read time: 12 min read
Understanding forward propagation and backpropagation through explicit formulas
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-18 | ⏱️ Read time: 12 min read
Understanding forward propagation and backpropagation through explicit formulas
#DataScience #AI #Python
❤1
📌 The Machine Learning “Advent Calendar” Day 19: Bagging in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-19 | ⏱️ Read time: 11 min read
Understanding ensemble learning from first principles in Excel
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-19 | ⏱️ Read time: 11 min read
Understanding ensemble learning from first principles in Excel
#DataScience #AI #Python
📌 Agentic AI Swarm Optimization using Artificial Bee Colonization (ABC)
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-19 | ⏱️ Read time: 27 min read
Using Agentic AI prompts with the Artificial Bee Colony algorithm to enhance unsupervised clustering and…
#DataScience #AI #Python
🗂 Category: AGENTIC AI
🕒 Date: 2025-12-19 | ⏱️ Read time: 27 min read
Using Agentic AI prompts with the Artificial Bee Colony algorithm to enhance unsupervised clustering and…
#DataScience #AI #Python
📌 How I Optimized My Leaf Raking Strategy Using Linear Programming
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-19 | ⏱️ Read time: 13 min read
From a weekend chore to a fun application of valuable operations research principles
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-19 | ⏱️ Read time: 13 min read
From a weekend chore to a fun application of valuable operations research principles
#DataScience #AI #Python
❤2
📌 Six Lessons Learned Building RAG Systems in Production
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-19 | ⏱️ Read time: 10 min read
Best practices for data quality, retrieval design, and evaluation in production RAG systems
#DataScience #AI #Python
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-19 | ⏱️ Read time: 10 min read
Best practices for data quality, retrieval design, and evaluation in production RAG systems
#DataScience #AI #Python
❤2
Forwarded from Machine Learning with Python
🚀Stanford just completed a must-watch for anyone serious about AI:
🎓 “𝗖𝗠𝗘 𝟮𝟵𝟱: 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 & 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀” is now live entirely on YouTube and it’s pure gold.
If you’re building your AI career, stop scrolling.
This isn’t another surface-level overview. It’s the clearest, most structured intro to LLMs you could follow, straight from the Stanford Autumn 2025 curriculum.
📚 𝗧𝗼𝗽𝗶𝗰𝘀 𝗰𝗼𝘃𝗲𝗿𝗲𝗱 𝗶𝗻𝗰𝗹𝘂𝗱𝗲:
• How Transformers actually work (tokenization, attention, embeddings)
• Decoding strategies & MoEs
• LLM finetuning (LoRA, RLHF, supervised)
• Evaluation techniques (LLM-as-a-judge)
• Optimization tricks (RoPE, quantization, approximations)
• Reasoning & scaling
• Agentic workflows (RAG, tool calling)
🧠 My workflow: I usually take the trannoscripts, feed them into NotebookLM, and once I’ve done the lectures, I replay them during walks or commutes. That combo works wonders for retention.
🎥 Watch these now:
- Lecture 1: https://lnkd.in/dDER-qyp
- Lecture 2: https://lnkd.in/dk-tGUDm
- Lecture 3: https://lnkd.in/drAPdjJY
- Lecture 4: https://lnkd.in/e_RSgMz7
- Lecture 5: https://lnkd.in/eivMA9pe
- Lecture 6: https://lnkd.in/eYwwwMXn
- Lecture 7: https://lnkd.in/eKwkEDXV
- Lecture 8: https://lnkd.in/eEWvyfyK
- Lecture 9: https://lnkd.in/euiKRGaQ
🗓 Do yourself a favor for this 2026: block 2-3 hours per week / llectue and go through them.
If you’re in AI — whether building infra, agents, or apps — this is the foundational course you don’t want to miss.
Let’s level up.
https://news.1rj.ru/str/CodeProgrammer😅
🎓 “𝗖𝗠𝗘 𝟮𝟵𝟱: 𝗧𝗿𝗮𝗻𝘀𝗳𝗼𝗿𝗺𝗲𝗿𝘀 & 𝗟𝗮𝗿𝗴𝗲 𝗟𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗠𝗼𝗱𝗲𝗹𝘀” is now live entirely on YouTube and it’s pure gold.
If you’re building your AI career, stop scrolling.
This isn’t another surface-level overview. It’s the clearest, most structured intro to LLMs you could follow, straight from the Stanford Autumn 2025 curriculum.
📚 𝗧𝗼𝗽𝗶𝗰𝘀 𝗰𝗼𝘃𝗲𝗿𝗲𝗱 𝗶𝗻𝗰𝗹𝘂𝗱𝗲:
• How Transformers actually work (tokenization, attention, embeddings)
• Decoding strategies & MoEs
• LLM finetuning (LoRA, RLHF, supervised)
• Evaluation techniques (LLM-as-a-judge)
• Optimization tricks (RoPE, quantization, approximations)
• Reasoning & scaling
• Agentic workflows (RAG, tool calling)
🧠 My workflow: I usually take the trannoscripts, feed them into NotebookLM, and once I’ve done the lectures, I replay them during walks or commutes. That combo works wonders for retention.
🎥 Watch these now:
- Lecture 1: https://lnkd.in/dDER-qyp
- Lecture 2: https://lnkd.in/dk-tGUDm
- Lecture 3: https://lnkd.in/drAPdjJY
- Lecture 4: https://lnkd.in/e_RSgMz7
- Lecture 5: https://lnkd.in/eivMA9pe
- Lecture 6: https://lnkd.in/eYwwwMXn
- Lecture 7: https://lnkd.in/eKwkEDXV
- Lecture 8: https://lnkd.in/eEWvyfyK
- Lecture 9: https://lnkd.in/euiKRGaQ
🗓 Do yourself a favor for this 2026: block 2-3 hours per week / llectue and go through them.
If you’re in AI — whether building infra, agents, or apps — this is the foundational course you don’t want to miss.
Let’s level up.
https://news.1rj.ru/str/CodeProgrammer
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📌 Understanding the Generative AI User
🗂 Category: PRODUCT MANAGEMENT
🕒 Date: 2025-12-20 | ⏱️ Read time: 11 min read
What do regular technology users think (and know) about AI?
#DataScience #AI #Python
🗂 Category: PRODUCT MANAGEMENT
🕒 Date: 2025-12-20 | ⏱️ Read time: 11 min read
What do regular technology users think (and know) about AI?
#DataScience #AI #Python
❤2
📌 EDA in Public (Part 2): Product Deep Dive & Time-Series Analysis in Pandas
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-20 | ⏱️ Read time: 9 min read
Learn how to analyze product performance, extract time-series features, and uncover key seasonal trends in…
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-20 | ⏱️ Read time: 9 min read
Learn how to analyze product performance, extract time-series features, and uncover key seasonal trends in…
#DataScience #AI #Python
❤1
📌 Tools for Your LLM: a Deep Dive into MCP
🗂 Category: LLM APPLICATIONS
🕒 Date: 2025-12-21 | ⏱️ Read time: 8 min read
MCP is a key enabler into turning your LLM into an agent by providing it…
#DataScience #AI #Python
🗂 Category: LLM APPLICATIONS
🕒 Date: 2025-12-21 | ⏱️ Read time: 8 min read
MCP is a key enabler into turning your LLM into an agent by providing it…
#DataScience #AI #Python
❤3
📌 How to Do Evals on a Bloated RAG Pipeline
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-21 | ⏱️ Read time: 71 min read
Comparing metrics across datasets and models
#DataScience #AI #Python
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-21 | ⏱️ Read time: 71 min read
Comparing metrics across datasets and models
#DataScience #AI #Python
❤1
🚀 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.
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🎯 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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📌 The Geometry of Laziness: What Angles Reveal About AI Hallucinations
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-22 | ⏱️ Read time: 12 min read
A story about failing forward, spheres you can’t visualize, and why sometimes the math knows…
#DataScience #AI #Python
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-22 | ⏱️ Read time: 12 min read
A story about failing forward, spheres you can’t visualize, and why sometimes the math knows…
#DataScience #AI #Python
❤1
📌 Understanding Vibe Proving
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-22 | ⏱️ Read time: 18 min read
How to make LLMs reason with verifiable, step-by-step logic (Part 1)
#DataScience #AI #Python
🗂 Category: LARGE LANGUAGE MODELS
🕒 Date: 2025-12-22 | ⏱️ Read time: 18 min read
How to make LLMs reason with verifiable, step-by-step logic (Part 1)
#DataScience #AI #Python
❤1
Forwarded from Machine Learning with Python
AI-ML Roadmap from Scratch
👉 https://github.com/aadi1011/AI-ML-Roadmap-from-scratch?tab=readme-ov-file
https://news.1rj.ru/str/CodeProgrammer🌟
Like and Share
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Like and Share
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📌 The Machine Learning “Advent Calendar” Day 22: Embeddings in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 8 min read
Understanding text embeddings through simple models and Excel
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 8 min read
Understanding text embeddings through simple models and Excel
#DataScience #AI #Python
📌 Synergy in Clicks: Harsanyi Dividends for E-Commerce
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-23 | ⏱️ Read time: 19 min read
A brief overview of the math behind the Harsanyi Dividend and a real-world application in…
#DataScience #AI #Python
🗂 Category: DATA SCIENCE
🕒 Date: 2025-12-23 | ⏱️ Read time: 19 min read
A brief overview of the math behind the Harsanyi Dividend and a real-world application in…
#DataScience #AI #Python
❤2
📌 The Machine Learning “Advent Calendar” Day 21: Gradient Boosted Decision Tree Regressor in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read
Gradient descent in function space with decision trees
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read
Gradient descent in function space with decision trees
#DataScience #AI #Python
❤1
📌 The Machine Learning “Advent Calendar” Day 20: Gradient Boosted Linear Regression in Excel
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read
From Random Ensembles to Optimization: Gradient Boosting Explained
#DataScience #AI #Python
🗂 Category: MACHINE LEARNING
🕒 Date: 2025-12-22 | ⏱️ Read time: 10 min read
From Random Ensembles to Optimization: Gradient Boosting Explained
#DataScience #AI #Python
❤1