Machine Learning

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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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الشبكة:Machine Learning with Python سوريا227 التكنولوجيات والتطبيقات3 364...

📈 نظرة تحليلية على قناة تيليجرام Machine Learning

تُعد قناة Machine Learning (@machinelearning9) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 40 145 مشتركاً، محتلاً المرتبة 3 364 في فئة التكنولوجيات والتطبيقات والمرتبة 227 في منطقة سوريا.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 40 145 مشتركاً.

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حالة التحقق: غير موثّقة
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وصول المنشورات: يحصل كل منشور على متوسط 785 مشاهدة. وخلال اليوم الأول يجمع عادةً 760 مشاهدة.
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📝 الوصف وسياسة المحتوى

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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”

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 28 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.

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Sepp Hochreiter, who invented LSTM 30+ year ago, gave a keynote talk at Neurips 2024 and introduced xLSTM (Extended Long Short-Term Memory). I designed this Excel exercise to help you understand how xLSTM works. More: https://www.byhand.ai/p/xlstm

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📌 How to Keep AI Costs Under Control 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-10-23 | ⏱️ Read time: 4 min read Lessons from Scaling LLMs

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📌 When Transformers Sing: Adapting SpectralKD for Text-Based Knowledge Distillation 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-10-23 | ⏱️ Read time: 8 min read Exploring the frequency fingerprints of Transformers to guide smarter knowledge distillation

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📌 Deploy an OpenAI Agent Builder Chatbot to a Website 🗂 Category: AGENTIC AI 🕒 Date: 2025-10-24 | ⏱️ Read time: 12 min read Using OpenAI’s Agent Builder ChatKit

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📌 Choosing the Best Model Size and Dataset Size under a Fixed Budget for LLMs 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-10-24 | ⏱️ Read time: 5 min read A small-scale exploration using Tiny Transformers

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📌 How to Consistently Extract Metadata from Complex Documents 🗂 Category: LLM APPLICATIONS 🕒 Date: 2025-10-24 | ⏱️ Read time: 8 min read Learn how to extract important pieces of information from your documents

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📌 Agentic AI from First Principles: Reflection 🗂 Category: AGENTIC AI 🕒 Date: 2025-10-24 | ⏱️ Read time: 21 min read From theory to code: building feedback loops that improve LLM accuracy

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📌 Building a Geospatial Lakehouse with Open Source and Databricks 🗂 Category: DATA ENGINEERING 🕒 Date: 2025-10-25 | ⏱️ Read time: 10 min read An example workflow for vector geospatial data science

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📌 Data Visualization Explained (Part 4): A Review of Python Essentials 🗂 Category: DATA SCIENCE 🕒 Date: 2025-10-25 | ⏱️ Read time: 8 min read Learn the foundations of Python to take your data visualization game to the next level.

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In Python, handling CSV files is straightforward using the built-in csv module for reading and writing tabular data, or pandas for advanced analysis—essential for data processing tasks like importing/exporting datasets in interviews.

# Reading CSV with csv module (basic)
import csv
with open('data.csv', 'r') as file:
    reader = csv.reader(file)
    data = list(reader)  # data = [['Name', 'Age'], ['Alice', '30'], ['Bob', '25']]

# Writing CSV with csv module
import csv
with open('output.csv', 'w', newline='') as file:
    writer = csv.writer(file)
    writer.writerow(['Name', 'Age'])  # Header
    writer.writerows([['Alice', 30], ['Bob', 25]])  # Data rows

# Advanced: Reading with pandas (handles headers, missing values)
import pandas as pd
df = pd.read_csv('data.csv')  # df = DataFrame with columns 'Name', 'Age'
print(df.head())  # Output: First 5 rows preview

# Writing with pandas
df.to_csv('output.csv', index=False)  # Saves without row indices

#python #csv #pandas #datahandling #fileio #interviewtips 👉 @DataScience4

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📌 Google’s Data Science Agent: Can It Really Do Your Job? 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-21 | ⏱️ Read time: 11 min read I tested Google’s Data Science Agent in Colab—here’s what it got right (and where it…

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📌 What Germany Currently Is Up To, Debt-Wise 🗂 Category: DATA SCIENCE 🕒 Date: 2025-03-21 | ⏱️ Read time: 6 min read Billions, visualized to scale using python and HTML

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📌 No More Tableau Downtime: Metadata API for Proactive Data Health 🗂 Category: DATA SCIENCE 🕒 Date: 2025-03-21 | ⏱️ Read time: 14 min read Leverage the power of the Metadata API to act on any potential data disruptions

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📌 Evolving Product Operating Models in the Age of AI 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-21 | ⏱️ Read time: 14 min read This article explores how the product operating model, and the core competencies of empowered product…

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📌 Build Your Own AI Coding Assistant in JupyterLab with Ollama and Hugging Face 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-24 | ⏱️ Read time: 8 min read A step-by-step guide to creating a local coding assistant without sending your data to the…

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📌 From Fuzzy to Precise: How a Morphological Feature Extractor Enhances AI’s Recognition Capabilities 🗂 Category: ARTIFICIAL INTELLIGENCE 🕒 Date: 2025-03-25 | ⏱️ Read time: 22 min read Mimicking human visual perception to truly understand objects

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📌 What Do Machine Learning Engineers Do? 🗂 Category: MACHINE LEARNING 🕒 Date: 2025-03-25 | ⏱️ Read time: 8 min read Breaking down my role as a machine learning engineer

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📌 Least Squares: Where Convenience Meets Optimality 🗂 Category: DATA SCIENCE 🕒 Date: 2025-03-25 | ⏱️ Read time: 11 min read Beyond being computationally easy, Least Squares is statically optimal and has a deep connection with…

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📌 Evaluating LLMs for Inference, or Lessons from Teaching for Machine Learning 🗂 Category: LARGE LANGUAGE MODELS 🕒 Date: 2025-06-02 | ⏱️ Read time: 12 min read It’s like grading papers, but your student is an LLM