Data Analytics
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Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making. Admin: @HusseinSheikho || @Hussein_Sheikho
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Network:📈 Analytical overview of Telegram channel Data Analytics
Channel Data Analytics (@dataanalyticsx) in the English language segment is an active participant. Currently, the community unites 30 560 subscribers, ranking 4 280 in the Technologies & Applications category and 20 902 in the Russia region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 30 560 subscribers.
According to the latest data from 05 October, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 582 over the last 30 days and by 24 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 5.28%. Within the first 24 hours after publication, content typically collects 1.16% reactions from the total number of subscribers.
- Post reach: On average, each post receives 1 612 views. Within the first day, a publication typically gains 355 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 3.
- Thematic interests: Content is focused on key topics such as sellerflash, buybox, buyer, chaos, effortless.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Thanks to the high frequency of updates (latest data received on 06 October, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.
30 560
Subscribers
+2424 hours
+1597 days
+58230 days
Posts Archive
30 560
Repost from Machine Learning with Python
🎓 $10,000 Scholarship Grant — Yours for the Taking! 🎓
Imagine this: $10,000 handed to you — completely FREE — to fund your education. No essays. No essays. No application fees. Just your effort inside our bot. 💸
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Here's how easy it is to earn points:
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30 560
Exporting the model from PyTorch to the universal ONNX format for independent inference 🚀
Deploying PyTorch models in production often requires installing a large framework and relying on a Python environment. The ONNX (Open Neural Network Exchange) format converts the computation graph into an intermediate binary format suitable for running on any device and programming language. We will export the PyTorch neural network and run its inference using the lightweight ONNX Runtime. 🛠
To export and run the neural network, we will install the PyTorch framework, the ONNX library, and the cross-platform ONNX Runtime engine.
pip install torch onnx onnxruntime.onnx file, and immediately performs a verification of the output.
import torch, torch.nn as nn, onnxruntime as ort, numpy as np
model = nn.Sequential(nn.Linear(10, 5), nn.ReLU())
x = torch.randn(1, 10)
torch.onnx.export(model, x, "model.onnx", input_names=["input"], output_names=["output"])
session = ort.InferenceSession("model.onnx")
res = session.run(None, {"input": x.numpy()})
print("ONNX Output shape:", res[0].shape)python3 -c "import onnx; model = onnx.load('model.onnx'); onnx.checker.check_model(model); print('ONNX Model Status: Valid')"rm -f model.onnx30 560
Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
30 560
Repost from Machine Learning with Python
+1
"How to Train a Neural Network" is a concise summary of the MIT course lectures on deep learning from 2024. It focuses on one of the fundamental questions in neural networks: how a model learns its weights.
The summary examines the training process from a mathematical perspective. It covers topics such as forward propagation, loss functions, gradients, backpropagation, and gradient-based optimization methods.
I believe this is an interesting resource for those who want to go beyond a general, intuitive understanding of neural networks and begin to delve into the mathematics that underlies their training.
https://ocw.mit.edu/courses/6-7960-deep-learning-fall-2024/mit6_7960_f24_lec2.pdf
https://t.me/CodeProgrammer 🤩
30 560
Когда нужна альтернатива биржам
Bitpapa — 1M+ Users
Крипторынок меняется, а вместе с ним меняются привычные способы покупки и обмена криптовалюты.
Bitpapa предлагает альтернативный формат: P2P-сделки, криптокошелёк и обмен BTC, USDT и других активов в одном месте.
Более 100 способов оплаты — чтобы выбрать удобный вариант для сделки.
Попробуй Bitpapa.
Ad. 18+
30 560
Repost from Machine Learning
Pandas vs Polars — 14-section course cheatshee
https://t.me/MachineLearning9
30 560
Repost from Machine Learning with Python
If you're just starting to learn machine learning and want to delve deeper into the mathematics required for machine learning and deep learning, I recommend trying this platform. It's something like LeetCode for machine learning.
This is not an advertisement: I personally used it and decided to share it with you.
https://deep-ml.com
https://t.me/CodeProgrammer
30 560
Repost from Machine Learning with Python
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
30 560
📊 Collecting Data Across Different Regions?
Data analysis often starts long before the dashboard or visualization.
When collecting public web data, regional differences can affect the content, prices, search results, or other information returned to your requests.
Using residential IPs from different locations can help when you need to test or collect location-specific data.
711Proxy provides:
🌍 100M+ real residential IPs
🌎 200+ countries & regions
🔄 Sticky sessions
🔌 SOCKS5 support
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Use 711TRIAL to get 1GB of residential proxy traffic for testing.
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After signing up, contact 711Proxy support and mention “711TRIAL” to claim your trial.
For eligible new users only.
30 560
Get Up to 500MB of Residential Proxy Traffic for Your Python Projects 🐍
Building a web scraper with Python?
ThorData helps developers collect public web data while handling proxy rotation, geo-targeting, and access restrictions.
✅ Residential IPs across 190+ countries
✅ Country, city, and ASN-level targeting
✅ Rotating and sticky sessions
✅ HTTP(S) and SOCKS5 support
✅ Works with Requests, Scrapy, Selenium, and Playwright
🎁 Exclusive offer for Machine Learning with Python members
Eligible new users can receive up to 500MB of residential proxy traffic for testing.
Use channel code: PYTHONSCRAPE
👉 Start your test:
https://www.thordata.com/?ls=MQiAFqAo&lk=ps-02
Available to eligible new users. The actual trial traffic may vary, up to a maximum of 500MB.
30 560
🚀Round 2 – 14-Day CCNA & CCNP Study Sprint!
Our first 21-Day Sprint was a huge success — we saw amazing check-ins, great discussions, and a community that truly learned together. 🙌
Now we're back with a faster, tighter 14-Day Sprint — same energy, same prizes, easier to finish! 💪
📅 Sprint Period: Sep 14 – Sep 27 (UTC+8)
📝 How It Works:
① DM admin: "I'M IN + cert name" (e.g., I'M IN CCNA 200-301)
② Check in 12 out of 14 days → win prizes 🎁
🏆 Prizes (First come, first served!):
1️⃣ $10 SPOTO Universal Coupon ×2
2️⃣ Cisco SD-Access Training ($150 value) ×1
3️⃣ Cisco SD-WAN Training ($150 value) ×1
4️⃣ CCNA Training Pro Package ($59.99 value) ×10
5️⃣ Free Cisco Learning Pack – unlimited for all finishers 🎁
✅ Referral Bonus: Invite a friend → Get FREE EXAM DEMO
💻 DM admin to register: https://wa.me/8619559123054
JOIN 14 Days Study Sprint: https://chat.whatsapp.com/KZrAj2HZ3Y5K9UhhNhrApf
30 560
Repost from Machine Learning
This repository contains Jupyter notebooks for the O'Reilly book "Transformers: The Definitive Guide."
It includes code for computer vision tasks, time series analysis, audio processing, and reinforcement learning.
https://github.com/Nicolepcx/transformers-the-definitive-guide
https://t.me/MachineLearning9 🤩
