Epython Lab@epythonlab P.1890

EPYTHONLAB Telegram 1890

📢Day 17/100: From Data to Insights

My journey started with collecting and cleaning data from Telegram channels, a hub for Ethiopian e-commerce.

Key steps:

1️⃣ Scraping Telegram messages to capture product details.

2️⃣ Preprocessing Amharic text to handle non-text characters and normalize content.

3️⃣ Tokenizing text for labeling.

💡 Takeaway: High-quality data preparation is the backbone of effective machine learning models.

#DataScience #AmharicNLP #FintechEthiopia

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834 viewsDec 19 at 04:39

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Create: 2024-12-19
Last Update: 2025-02-04 02:34:00

📢Day 17/100: From Data to Insights

My journey started with collecting and cleaning data from Telegram channels, a hub for Ethiopian e-commerce.

Key steps:

1️⃣ Scraping Telegram messages to capture product details.

2️⃣ Preprocessing Amharic text to handle non-text characters and normalize content.

3️⃣ Tokenizing text for labeling.

💡 Takeaway: High-quality data preparation is the backbone of effective machine learning models.

#DataScience #AmharicNLP #FintechEthiopia

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Date: 2025-02-04|

Telegram message that reads: "Bear Market Screaming Therapy Group. You are only allowed to send screaming voice notes. Everything else = BAN. Text pics, videos, stickers, gif = BAN. Anything other than screaming = BAN. You think you are smart = BAN. The imprisonment came as Telegram said it was "surprised" by claims that privacy commissioner Ada Chung Lai-ling is seeking to block the messaging app due to doxxing content targeting police and politicians. Your posting frequency depends on the topic of your channel. If you have a news channel, it’s OK to publish new content every day (or even every hour). For other industries, stick with 2-3 large posts a week. Administrators Select “New Channel”
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