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We will leave a link with free entry to a channel that draws money every day. Each subscriber gets between $100 and $5,000.
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Dataset Name: Style Color Images
🔍 Brand and Product Recognition
🚀 💡 The main dataset (style.zip) is 2184 color images (150x150x3) with 7 brands and 10 products, and the file with labels style.csv.
Photo files are in the .png format and the labels are integers and values.
🤌 From: Kaggle
🤖 Size: 343 MB
🔵 https://t.me/datasets1
Photo files are in the .png format and the labels are integers and values.
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TON is Hosting Three-Day Offline Marathons for Developers in 13 Cities Worldwide
TON (The Open Network), a blockchain integrated into Telegram, is currently holding the largest hackathon in its history, “The Open League Hackathon,” with a prize pool of $2,000,000!
To support the hackathon, TON Society is organizing offline events around the world, giving Web3 enthusiasts the opportunity to spend three days immersed in development and networking.
📍 The marathons will take place in Prague, Berlin, Kyiv, Warsaw, Tbilisi, Belgrade, Seoul, Taipei (Taiwan), Gurugram (India), Hong Kong, Minsk, Moscow, and Saint Petersburg. The first events start on May 24th, so hurry up and register!
🔥 Why you should participate:
— 3 days of networking, lectures, competitions, and working on your own projects with continuous support from TON Foundation representatives and teams from the TON ecosystem. You can also join online.
— $5,000 prize for the top three projects at each offline event + plenty of merchandise and other bonuses.
Don’t miss the chance to present your mini-application to 900 million active Telegram users with TON.
Check the marathon schedule and details here - sign up and don't miss out on this great opportunity!
For guaranteed application review and other inquiries, contact the community manager @kate_shuffle
TON (The Open Network), a blockchain integrated into Telegram, is currently holding the largest hackathon in its history, “The Open League Hackathon,” with a prize pool of $2,000,000!
To support the hackathon, TON Society is organizing offline events around the world, giving Web3 enthusiasts the opportunity to spend three days immersed in development and networking.
📍 The marathons will take place in Prague, Berlin, Kyiv, Warsaw, Tbilisi, Belgrade, Seoul, Taipei (Taiwan), Gurugram (India), Hong Kong, Minsk, Moscow, and Saint Petersburg. The first events start on May 24th, so hurry up and register!
🔥 Why you should participate:
— 3 days of networking, lectures, competitions, and working on your own projects with continuous support from TON Foundation representatives and teams from the TON ecosystem. You can also join online.
— $5,000 prize for the top three projects at each offline event + plenty of merchandise and other bonuses.
Don’t miss the chance to present your mini-application to 900 million active Telegram users with TON.
Check the marathon schedule and details here - sign up and don't miss out on this great opportunity!
For guaranteed application review and other inquiries, contact the community manager @kate_shuffle
TON
Your Digital Passport in TON Ecosystem
Build your reputation with every app you use and every contribution you make.
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Forwarded from Machine Learning with Python
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🔒 Dataset Name: Brent Oil Prices
🔍 Daily historical Brent Oil Prices available on the U.S. Energy Information Admin
🚀 The data contains daily Brent oil prices from 17th of May 1987 until the 13th of November 2022.
💡 The aim of this dataset and work is to predict future Crude Oil Prices based on the historical data available in the dataset.
🤌 From: Kaggle
🤖 Size: 38.8 kB
🔵 https://t.me/datasets1
🔍 Daily historical Brent Oil Prices available on the U.S. Energy Information Admin
🚀 The data contains daily Brent oil prices from 17th of May 1987 until the 13th of November 2022.
💡 The aim of this dataset and work is to predict future Crude Oil Prices based on the historical data available in the dataset.
🤌 From: Kaggle
🤖 Size: 38.8 kB
🔵 https://t.me/datasets1
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Are you ready to release the Spotify Songs Album dataset?
Anonymous Poll
42%
Yes 🙃
7%
Yessss ☺️
52%
Yesssssss 😍
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🔒 Dataset Name: Spotify Songs Album
🔍 This dataset provides concise details about music tracks and their performance across various platforms. It includes essential information like track name, artist(s), release date, and presence in popular playlists and charts on platforms like Spotify, Apple Music, Deezer, and Shazam. Additionally, it features metrics such as BPM, key, mode, danceability, valence, energy, acousticness, instrumentalness, and liveness_speechiness, which offer insights into the musical characteristics and appeal of each track.
💡 With this data, analysts can evaluate the popularity, genre, and audience engagement of different music offerings across multiple streaming services.
🤌 From: Kaggle
🤖 Size: 47.1 kB
🔵 https://t.me/datasets1
🔍 This dataset provides concise details about music tracks and their performance across various platforms. It includes essential information like track name, artist(s), release date, and presence in popular playlists and charts on platforms like Spotify, Apple Music, Deezer, and Shazam. Additionally, it features metrics such as BPM, key, mode, danceability, valence, energy, acousticness, instrumentalness, and liveness_speechiness, which offer insights into the musical characteristics and appeal of each track.
💡 With this data, analysts can evaluate the popularity, genre, and audience engagement of different music offerings across multiple streaming services.
🤌 From: Kaggle
🤖 Size: 47.1 kB
🔵 https://t.me/datasets1
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🔒 Dataset Name: Employee Data Analysis
🔍 Unlocking Insights for a Thriving Workplace
🚀 Our extensive collection of datasets provides a deep dive into different aspects of employee engagement and organizational dynamics.
💡 Our extensive collection of datasets provides a deep dive into different aspects of employee engagement and organizational dynamics.
🤌 From: Kaggle
🤖 Size: 120 kB
🔵 https://t.me/datasets1
🔍 Unlocking Insights for a Thriving Workplace
🚀 Our extensive collection of datasets provides a deep dive into different aspects of employee engagement and organizational dynamics.
💡 Our extensive collection of datasets provides a deep dive into different aspects of employee engagement and organizational dynamics.
🤌 From: Kaggle
🤖 Size: 120 kB
🔵 https://t.me/datasets1
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https://t.me/Hamster_kombat_bot/start?startapp=kentId418788114
💵 2 thousand coins as a gift for the first time
☄️ 25 thousand coins if you have Telegram Premium
Hamster will be listed on Ton Network soon
The experience is quite similar to that of the NOTCOIN bot💠
Hamster will be listed on Ton Network soon
The experience is quite similar to that of the NOTCOIN bot
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Telegram
Hamster Verse
Description: Welcome to the HamsterVerse!
Play, have fun, and earn $HMSTR in the amazing games across our ecosystem.
Big updates are coming soon!
Play, have fun, and earn $HMSTR in the amazing games across our ecosystem.
Big updates are coming soon!
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🔒 Dataset Name: LLMs Data (2018-2024)
🔍 Every major LLM and chatbot released since 2018 with parameters, tokens, etc.
🚀 This table includes specifications for various language models. The columns include the model name, the developing company, the model's architecture (e.g., Transformer or RNN), the number of parameters and tokens in billions (some are TBA), the ratio of parameters to tokens (specified only for Olympus), the ALScore (calculated as the square root of the product of parameters and tokens), the training dataset, the release date, additional notes, and a link to a website for interacting with the model.
🤌 From: Kaggle
🤖 Size: 22.8 kB
💋 https://t.me/datasets1
🔍 Every major LLM and chatbot released since 2018 with parameters, tokens, etc.
🚀 This table includes specifications for various language models. The columns include the model name, the developing company, the model's architecture (e.g., Transformer or RNN), the number of parameters and tokens in billions (some are TBA), the ratio of parameters to tokens (specified only for Olympus), the ALScore (calculated as the square root of the product of parameters and tokens), the training dataset, the release date, additional notes, and a link to a website for interacting with the model.
🤌 From: Kaggle
🤖 Size: 22.8 kB
💋 https://t.me/datasets1
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