🔒 Dataset Name: Loan-Dataset

🔍 About the status of the loan based on different parameters

🚀 This dataset contains information about customer loans, including customer demographics, loan details, and default status. The dataset can be used for various data analysis and machine learning tasks, such as predicting loan default risk.

🤌 From: Kaggle

🤖 Size: 430 kB

✅️ https://t.me/datasets1

Dataset Name: Loan-Dataset

https://t.me/datasets1 🧠

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🔒 Dataset Name: Loan-DatasetPatient Ratings: Identifying Best Drugs!

🔍 Analyzing reviews to reveal the top-rated medications

🚀 The dataset sourced from Druglib.com And Drugs.com, The dataset contains patient reviews on specific drugs along with related conditions. The reviews are categorized into reports on three aspects: benefits, side effects, and overall comments. Additionally, ratings are provided for overall satisfaction, side effects (on a 5-step scale), and effectiveness (on a 5-step scale).

🤌 From: Kaggle

🤖 Size: 42 MB

👀 https://t.me/datasets1

Dataset Name: Patient Ratings: Identifying Best Drugs!

https://t.me/datasets1 🧠

🖼 Dataset Name: Employee Attrition Classification Dataset
   
🔍 An In-Depth Synthetic Simulation for Attrition Analysis and Prediction
   
🚀 contains detailed information about various aspects of an employee's profile, including demographics, job-related features, and personal circumstances.

🌸This dataset is ideal for HR analytics, machine learning model development, and demonstrating advanced data analysis techniques. It provides a comprehensive and realistic view of the factors affecting employee retention, making it a valuable resource for researchers and practitioners in the field of human resources and organizational development

🤌 From: Kaggle      
      
🤖 Size: 1.7 MB       
   
👀 https://t.me/datasets1

Dataset Name: Employee Attrition Classification Dataset
    
https://t.me/datasets1 🧠

WebScraping with Gen AI

During this session, we'll explore the following topics:

1️⃣ Basics of Web Scraping:
Understand the fundamental concepts and techniques of web scraping and its legal and ethical considerations.

2️⃣ Scraping with Gen AI:
Discover how Gen AI revolutionizes the web scraping landscape with real-world examples.

3️⃣ Jina Reader API:
Get acquainted with the Jina Reader API, a powerful tool for obtaining LLM-friendly input from URLs or web searches.

4️⃣ ScrapeGraphAI:
Dive into ScrapeGraphAI, a groundbreaking Python library that combines LLMs and direct graph logic for creating robust scraping pipelines.

Event Details:
🗓 Date: 22 June, Saturday
⏰ Time: 11:00 AM IST
🔗 Register now: https://www.buildfastwithai.com/events/web-scraping-with-gen-ai

Connect with Founder from IIT Delhi;
https://www.linkedin.com/in/satvik-paramkusham/

🔒 Dataset Name: Instagram fake spammer genuine accounts
   
📅 Predict whether an Instagram user is fake/spammer or not
   
🚀  accounts included in this dataset after carefully examining each instance and as such the dataset has high level of accuracy though there might be a couple of misidentified accounts in the spammers list as well.

🤌 From: Kaggle      
      
🤖 Size: 6.8 KB       
   
😠 https://t.me/datasets1

Dataset Name: Instagram fake spammer genuine accounts
    
https://t.me/datasets1 🧠

🔒 Dataset Name: Instagram fake spammer genuine accounts
   
📈Samsung Stock Analysis : 2000 to Today.
   
🚀  It includes essential columns such as the date, opening price, highest price of the day, lowest price of the day, closing price, adjusted closing price, and trading volume.

📱This extensive data is invaluable for conducting historical analyses, forecasting future stock performance, and understanding long-term market trends related to Samsung Electronics' stock.

🎲 From: Kaggle      
      
🤖 Size: 114.3 KB       
   
🟡 https://t.me/datasets1

Dataset Name: Samsung Stock Price Dataset
    
https://t.me/datasets1 🧠

🔒 Dataset Name: Women's E-Commerce Clothing Reviews
   
👙 23k reviews with 10 feature variables about women´s clothing
   
🚀  This is a Women’s Clothing E-Commerce dataset revolving around the reviews written by customers. Its nine supportive features offer a great environment to parse out the text through its multiple dimensions. Because this is real commercial data, it has been anonymized, and references to the company in the review text and body have been replaced with “retailer”.

🎲 From: Kaggle      
      
🤖 Size: 2.8 MB       
   
🟡 https://t.me/datasets1

Dataset Name: Women's E-Commerce Clothing Reviews
    
https://t.me/datasets1 🧠

🔒 Dataset Name: Predict Online Dating Matches Dataset

https://t.me/datasets1 🧠