📦 Datasets name: Diamond dataset


🌸 This classic dataset contains the prices and other attributes of almost 54,000 diamonds. It's a great dataset for beginners learning to work with data analysis and visualization.


🌐 Format: CSV file

🔐 From: Kaggle

👀 https://t.me/datasets1

✅ Dataset Name: Datasets for ear detection and recognition 👇

🤌 From: Kaggle

🙌 Format: Images

🤖 Size: 275 MB

✅ https://t.me/datasets1

☄️ Dataset Name: Datasets for ear detection and recognition

🟢 https://t.me/datasets1

🇸🇾 Dataset Name: Gender Classification Dataset

🗯 Male Female image dataset

📢 Content: The data set is of cropped images of male and female . It is split into training and validation directory. Training contains ~23,000 images of each class and validation directory contains ~5,500 images of each class. 👇

🤌 From: Kaggle

🙌 Format: Images

🤖 Size: 270 MB

✅ https://t.me/datasets1

🔔 Dataset Name: Dataset Name: Gender Classification Dataset

🔵 https://t.me/datasets1

🔔 Dataset Name: Crude Oil Price Prediction

🔵 https://t.me/datasets1

🔔 Dataset Name: Satellite Images to predict poverty



⭐️ High-resolution satellite imagery is increasingly available at the global scale and contains an abundance of information about landscape features that could be correlated with economic activity. Unfortunately, such data are highly unstructured and thus challenging to extract meaningful insights from at scale, even with intensive manual analysis. Recent applications of deep learning techniques to large-scale image data sets have led to marked improvements in fundamental computer vision tasks such as object detection and classification, but these techniques are generally most effective in supervised learning
regimes where labelled training data are abundant.


🌸 This data set contains 3 zip folders having a total of 32823 images. Ethiopia, Malawi and Nigeria are the 3 countries. Each folder contains images of the respective countries.


🤌 From: Kaggle

🙌 Format: images

🤖 Size: 6 GB


🔵 https://t.me/datasets1

🔔 Dataset Name: Password Dataset


🌺Project Goal: Predict password strength (strong, medium, weak) based on data

🌺 Data Source: User registration data (passwords) from Facebook APIs


🌺Use Case: Determine the strength level of a password entered during user registration

🌺 Model Creation Process:

-Data preprocessing and analysis
-Application of natural language processing (NLP) and machine learning techniques

🤌 From: Kaggle

🙌 Format: SQL

🤖 Size: 1.9 MB

🔵 https://t.me/datasets1

🔔 Dataset Name: Password Dataset


🔵 https://t.me/datasets1