Greetings to our dear friends and followers,
To increase engagement with you and elevate your projects, we’ve prepared an exciting opportunity! 🎉 If you’ve completed a project using the datasets shared on our channel, feel free to send us the link to your project or GitHub repository. 💻
We will showcase the best projects on our channel so that others, especially engineers and specialists, can view and review them. 🔍 This will not only give your project greater visibility, but you can also benefit from valuable feedback, ratings, and even stars from others. 🌟 Your project might even become a source of inspiration for others! 💡
Don’t miss this fantastic opportunity and join us on the path to more visibility. 🚀
We’re eagerly waiting to see your masterpieces! 🎨
Best regards,
@HusseinSheikho
To increase engagement with you and elevate your projects, we’ve prepared an exciting opportunity! 🎉 If you’ve completed a project using the datasets shared on our channel, feel free to send us the link to your project or GitHub repository. 💻
We will showcase the best projects on our channel so that others, especially engineers and specialists, can view and review them. 🔍 This will not only give your project greater visibility, but you can also benefit from valuable feedback, ratings, and even stars from others. 🌟 Your project might even become a source of inspiration for others! 💡
Don’t miss this fantastic opportunity and join us on the path to more visibility. 🚀
We’re eagerly waiting to see your masterpieces! 🎨
Best regards,
@HusseinSheikho
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🔒 Dataset Name: US Stock Market and Commodities Data (2020-2024)
♦️ Comprehensive Daily Data Covering Stocks, Commodities, and Cryptocurrencies
🚀 This dataset includes 39 columns, covering a broad spectrum of financial data points such as prices and volumes of major stocks, indices, commodities, and cryptocurrencies. The data is presented in a structured CSV file format, making it easily accessible and usable for various financial analyses, market research, and predictive modeling. This dataset is ideal for anyone looking to gain insights into the trends and movements within the US financial markets during this period, including the impact of major global events.
🎲 From: Kaggle
🤖 Size: 123.1 MB
🔄 https://news.1rj.ru/str/datasets1
♦️ Comprehensive Daily Data Covering Stocks, Commodities, and Cryptocurrencies
🚀 This dataset includes 39 columns, covering a broad spectrum of financial data points such as prices and volumes of major stocks, indices, commodities, and cryptocurrencies. The data is presented in a structured CSV file format, making it easily accessible and usable for various financial analyses, market research, and predictive modeling. This dataset is ideal for anyone looking to gain insights into the trends and movements within the US financial markets during this period, including the impact of major global events.
🎲 From: Kaggle
🤖 Size: 123.1 MB
🔄 https://news.1rj.ru/str/datasets1
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CelebFaces Attributes (CelebA) Dataset
Over 200k images of celebrities with 40 binary attribute annotations
Content
Overall
202,599 number of face images of various celebrities
10,177 unique identities, but names of identities are not given
40 binary attribute annotations per image
5 landmark locations
Data Files
img_align_celeba.zip: All the face images, cropped and aligned
list_eval_partition.csv: Recommended partitioning of images into training, validation, testing sets. Images 1-162770 are training, 162771-182637 are validation, 182638-202599 are testing
list_bbox_celeba.csv: Bounding box information for each image. "x_1" and "y_1" represent the upper left point coordinate of bounding box. "width" and "height" represent the width and height of bounding box
list_landmarks_align_celeba.csv: Image landmarks and their respective coordinates. There are 5 landmarks: left eye, right eye, nose, left mouth, right mouth
list_attr_celeba.csv: Attribute labels for each image. There are 40 attributes. "1" represents positive while "-1" represents negative
https://news.1rj.ru/str/datasets1🌈 🌈
Over 200k images of celebrities with 40 binary attribute annotations
Content
Overall
202,599 number of face images of various celebrities
10,177 unique identities, but names of identities are not given
40 binary attribute annotations per image
5 landmark locations
Data Files
img_align_celeba.zip: All the face images, cropped and aligned
list_eval_partition.csv: Recommended partitioning of images into training, validation, testing sets. Images 1-162770 are training, 162771-182637 are validation, 182638-202599 are testing
list_bbox_celeba.csv: Bounding box information for each image. "x_1" and "y_1" represent the upper left point coordinate of bounding box. "width" and "height" represent the width and height of bounding box
list_landmarks_align_celeba.csv: Image landmarks and their respective coordinates. There are 5 landmarks: left eye, right eye, nose, left mouth, right mouth
list_attr_celeba.csv: Attribute labels for each image. There are 40 attributes. "1" represents positive while "-1" represents negative
https://news.1rj.ru/str/datasets1
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🔒 Dataset Name: Web Network Traffic
🚦Network traffic for classification of good or bad request
🚀 This dataset contains network traffic logs captured by Burp-Suite, aimed at classifying web requests as either good or bad based on their characteristics. The dataset is designed for the task of predicting whether incoming requests are legitimate (good) or malicious (bad), aiding in the detection and prevention of web-based attacks.
🎲 From: Kaggle
🤖 Size: 112.3 KB
🔄 https://news.1rj.ru/str/datasets1
🚦Network traffic for classification of good or bad request
🚀 This dataset contains network traffic logs captured by Burp-Suite, aimed at classifying web requests as either good or bad based on their characteristics. The dataset is designed for the task of predicting whether incoming requests are legitimate (good) or malicious (bad), aiding in the detection and prevention of web-based attacks.
🎲 From: Kaggle
🤖 Size: 112.3 KB
🔄 https://news.1rj.ru/str/datasets1
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🔒 Dataset Name: Amazon Phone Data: Prices, Ratings & Sales Insight
♦️Real-time data on phone prices, ratings, and sales trends for analysis
🚀 This dataset provides comprehensive real-time information on 340 phone products from Amazon, collected using the "Real-Time Amazon Data" API. The data covers various attributes such as product noscripts, prices, ratings, availability, and sales volume, offering a valuable resource for e-commerce analysis, machine learning projects, and consumer behavior studies focused on mobile phones.
🎲 From: Kaggle
🤖 Size: 30.4 kB
🔄 https://news.1rj.ru/str/datasets1
♦️Real-time data on phone prices, ratings, and sales trends for analysis
🚀 This dataset provides comprehensive real-time information on 340 phone products from Amazon, collected using the "Real-Time Amazon Data" API. The data covers various attributes such as product noscripts, prices, ratings, availability, and sales volume, offering a valuable resource for e-commerce analysis, machine learning projects, and consumer behavior studies focused on mobile phones.
🎲 From: Kaggle
🤖 Size: 30.4 kB
🔄 https://news.1rj.ru/str/datasets1
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Amazon Phone Data.zip
30.4 KB
Datasets Name: Amazon Phone Data: Prices, Ratings & Sales Insight
https://news.1rj.ru/str/datasets1 ❤️
https://news.1rj.ru/str/datasets1 ❤️
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Cat Dataset 😻
Over 9,000 images of cats with annotated facial features
Context:
The CAT dataset includes over 9,000 cat images. For each image, there are annotations of the head of cat with nine points, two for eyes, one for mouth, and six for ears.
🎲 From: Kaggle
🤖 Size: 4.04 GB
🔃 https://news.1rj.ru/str/datasets1
Over 9,000 images of cats with annotated facial features
Context:
The CAT dataset includes over 9,000 cat images. For each image, there are annotations of the head of cat with nine points, two for eyes, one for mouth, and six for ears.
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@codeprogrammer Helpful Cheat Sheets Compilation.zip
5.2 MB
Including Pandas, NumPy, Matplotlib, Seaborn, and others
Is it useful to you
http://t.me/codeprogrammer
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Forwarded from Machine Learning with Python
LOOKING FOR A NEW SOURCE OF INCOME?
Average earnings from 100$ a day
Lisa is looking for people who want to earn money. If you are responsible, motivated and want to change your life. Welcome to her channel.
WHAT YOU NEED TO WORK:
1. phone or computer
2. Free 15-20 minutes a day
3. desire to earn
❗️ Requires 20 people ❗️
Access is available at the link below
👇
https://news.1rj.ru/str/+NhwYZAXFlT8yZDIx
Average earnings from 100$ a day
Lisa is looking for people who want to earn money. If you are responsible, motivated and want to change your life. Welcome to her channel.
WHAT YOU NEED TO WORK:
1. phone or computer
2. Free 15-20 minutes a day
3. desire to earn
❗️ Requires 20 people ❗️
Access is available at the link below
👇
https://news.1rj.ru/str/+NhwYZAXFlT8yZDIx
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Daily_Dose_Of_Data_Science_Full_Archive.pdf
88.3 MB
Here’s the 2024 edition of the Daily Dose of Data Science archive.
Is it useful to you❓ , Like 👍
📂 Tags: #DataScience #Python #ML
http://t.me/codeprogrammer⭐️
Is it useful to you
http://t.me/codeprogrammer
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Data set containing bitcoin transactions graph metadata (2011-2013)
https://news.1rj.ru/str/datasets1
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Medical Deepfakes: Lung Cancer.
CT scans tampered with cancer added or removed. Can you find them?
The dataset consists 100 CT scans of two sets (80 scans and 20 scans). The first 80 were used in a blind trial with the radiologists (they weren't told they were tampered), and the 20 scans were used in an open trial with the radiologists (they were told the truth and asked to identify them).
For each experiment there is a csv table containing the ground truth. Each row in the csv indicates where a real, fake, or removed cancer is located (x, y, and z [slice#]) and its classification. There are four classes:
Class Acronym Denoscription
True-Benign TB: A location that actually has no cancer
True-Malicious TM: A location that has real cancer
False-Benign FB: A location that has real cancer, but it was removed.
False-Malicious FM: A location that does not have cancer, but fake cancer was injected there.
CT scans tampered with cancer added or removed. Can you find them?
The dataset consists 100 CT scans of two sets (80 scans and 20 scans). The first 80 were used in a blind trial with the radiologists (they weren't told they were tampered), and the 20 scans were used in an open trial with the radiologists (they were told the truth and asked to identify them).
For each experiment there is a csv table containing the ground truth. Each row in the csv indicates where a real, fake, or removed cancer is located (x, y, and z [slice#]) and its classification. There are four classes:
Class Acronym Denoscription
True-Benign TB: A location that actually has no cancer
True-Malicious TM: A location that has real cancer
False-Benign FB: A location that has real cancer, but it was removed.
False-Malicious FM: A location that does not have cancer, but fake cancer was injected there.
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