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Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

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Machine Learning (@machinelearning9) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 40 072 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 3 398-o'rinni va Suriya mintaqasida 232-o'rinni egallagan.

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“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

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📌 Hallucinations in LLMs Are Not a Bug in the Data 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-03-16 | ⏱️ Read time: 10 min read It’s a feature of the architecture #DataScience #AI #Python

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📌 Bayesian Thinking for People Who Hated Statistics 🗂 Category: DATA SCIENCE 🕒 Date: 2026-03-16 | ⏱️ Read time: 12 min read You already think like a Bayesian. Your stats class just taught the formula before the… #DataScience #AI #Python

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📌 The Causal Inference Playbook: Advanced Methods Every Data Scientist Should Master 🗂 Category: DATA SCIENCE 🕒 Date: 2026-03-15 | ⏱️ Read time: 17 min read Master six advanced causal inference methods with Python: doubly robust estimation, instrumental variables, regression discontinuity,… #DataScience #AI #Python

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📌 The 2026 Data Mandate: Is Your Governance Architecture a Fortress or a Liability? 🗂 Category: DATA GOVERNANCE 🕒 Date: 2026-03-15 | ⏱️ Read time: 8 min read Is your data strategy 2026-ready? Get a deep dive into the mandatory shift toward human-in-the-loop… #DataScience #AI #Python

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📌 The Current Status of The Quantum Software Stack 🗂 Category: QUANTUM COMPUTING 🕒 Date: 2026-03-14 | ⏱️ Read time: 8 min read How do we program quantum computers today? #DataScience #AI #Python

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📌 The Multi-Agent Trap 🗂 Category: AGENTIC AI 🕒 Date: 2026-03-14 | ⏱️ Read time: 12 min read Google DeepMind found multi-agent networks amplify errors 17x. Learn 3 architecture patterns that separate $60M… #DataScience #AI #Python

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📌 Personalized Restaurant Ranking with a Two-Tower Embedding Variant 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-03-13 | ⏱️ Read time: 6 min read How a lightweight two-tower model improved restaurant discovery when popularity ranking failed #DataScience #AI #Python

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📌 How Vision Language Models Are Trained from “Scratch” 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-03-13 | ⏱️ Read time: 13 min read A deep dive into exactly how text-only language models are finetuned to see images #DataScience #AI #Python

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📌 Why Care About Prompt Caching in LLMs? 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-03-13 | ⏱️ Read time: 11 min read Optimizing the cost and latency of your LLM calls with Prompt Caching #DataScience #AI #Python

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Repost from Machine Learning with Python

🗂 Building our own mini-Skynet — a collection of 10 powerful AI repositories from big tech companies 1. Generative AI for Beginners and AI Agents for Beginners Microsoft provides a detailed explanation of generative AI and agent architecture: from theory to practice. 2. LLMs from Scratch Step-by-step assembly of your own GPT to understand how LLMs are structured "under the hood". 3. OpenAI Cookbook An official set of examples for working with APIs, RAG systems, and integrating AI into production from OpenAI. 4. Segment Anything and Stable Diffusion Classic tools for computer vision and image generation from Meta and the CompVis research team. 5. Python 100 Days and Python Data Science Handbook A powerful resource for Python and data analysis. 6. LLM App Templates and ML for Beginners Ready-made app templates with LLMs and a structured course on classic machine learning. If you want to delve deeply into AI or start building your own projects — this is an excellent starting kit. tags: #github #LLM #AI #ML ➡️ https://t.me/CodeProgrammer

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📌 How to Build Agentic RAG with Hybrid Search 🗂 Category: RAG 🕒 Date: 2026-03-13 | ⏱️ Read time: 7 min read Learn how to build a powerful agentic RAG system #DataScience #AI #Python

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📌 A Tale of Two Variances: Why NumPy and Pandas Give Different Answers 🗂 Category: DATA SCIENCE 🕒 Date: 2026-03-13 | ⏱️ Read time: 7 min read Imagine you are analyzing a small dataset: You want to calculate some summary statistics to… #DataScience #AI #Python

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📌 I Finally Built My First AI App (And It Wasn’t What I Expected) 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-03-12 | ⏱️ Read time: 14 min read A beginner-friendly walkthrough of API calls, environment variables, and real-world AI infrastructure #DataScience #AI #Python

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📌 Scaling Vector Search: Comparing Quantization and Matryoshka Embeddings for 80% Cost Reduction 🗂 Category: MACHINE LEARNING 🕒 Date: 2026-03-12 | ⏱️ Read time: 11 min read Navigating the performance cliff: How pairing MRL with int8 and binary quantization balances infrastructure costs… #DataScience #AI #Python

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📌 Solving the Human Training Data Problem 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2026-03-12 | ⏱️ Read time: 18 min read How AI has completely transformed the way I study as a graduate student #DataScience #AI #Python

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Repost from Machine Learning with Python

Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A

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Repost from Machine Learning with Python

Machine Learning in Python (Course Notes) I just went through an amazing resource on #MachineLearning in #Python by 365 Data Science, and I had to share the key takeaways with you! Here’s what you’ll learn: 🔘 Linear Regression - The foundation of predictive modeling 🔘 Logistic Regression - Predicting probabilities and classifications 🔘 Clustering (K-Means, Hierarchical) - Making sense of unstructured data 🔘 Overfitting vs. Underfitting - The balancing act every ML engineer must master 🔘 OLS, R-squared, F-test - Key metrics to evaluate your models https://t.me/CodeProgrammer || Share 🌐 and Like 👍

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📌 Exploratory Data Analysis for Credit Scoring with Python 🗂 Category: DATA SCIENCE 🕒 Date: 2026-03-12 | ⏱️ Read time: 16 min read Understanding default risk through statistical analysis of borrower and loan characteristics. #DataScience #AI #Python