اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
Machine Learning
رفتن به کانال در Telegram
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
نمایش بیشتر📈 تحلیل کانال تلگرام Machine Learning
کانال Machine Learning (@machinelearning9) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 40 145 مشترک است و جایگاه 3 364 را در دسته فناوری و برنامهها و رتبه 227 را در منطقه سوريا دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 40 145 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 27 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر 412 و در ۲۴ ساعت گذشته برابر 5 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 1.96% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 1.89% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 785 بازدید دریافت میکند. در اولین روز معمولاً 760 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 2 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند distance, insidead, gpu, learning, degree تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 28 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامهها تبدیل کردهاند.
40 145
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آرشیو پست ها
40 145
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40 145
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
40 145
📌 How to Keep AI Costs Under Control
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2025-10-23 | ⏱️ Read time: 4 min read
Lessons from Scaling LLMs
40 145
📌 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
40 145
📌 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
40 145
📌 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
40 145
📌 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
40 145
📌 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
40 145
📌 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
40 145
📌 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
40 145
📌 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…
40 145
📌 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
40 145
📌 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…
40 145
📌 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…
40 145
📌 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
40 145
📌 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
40 145
📌 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…
40 145
📌 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
