shaadclt/Doctor-Scheduling-Agent-LlamaIndex

Language: Jupyter Notebook - Size: 200 KB - Last synced at: 8 days ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/EvalRAG

A comprehensive evaluation toolkit for assessing Retrieval-Augmented Generation (RAG) outputs using linguistic, semantic, and fairness metrics

Language: Python - Size: 32.2 KB - Last synced at: 8 days ago - Pushed at: 3 months ago - Stars: 4 - Forks: 0

shaadclt/BusinessCard-DataExtraction-OCR-NER

This project aims to extract structured data from business cards using a combination of OpenCV, PyTesseract, and spaCy.

Language: Python - Size: 10.4 MB - Last synced at: 17 days ago - Pushed at: almost 2 years ago - Stars: 6 - Forks: 0

shaadclt/Multi-Agent-System-LangGraph

This project demonstrates a multi-agent chatbot system built using LangGraph, LangChain, and Azure OpenAI GPT-4o. It enables intelligent routing of user queries to specialized agents .

Language: Jupyter Notebook - Size: 81.1 KB - Last synced at: 8 days ago - Pushed at: 3 months ago - Stars: 4 - Forks: 0

shaadclt/Text-Analysis-NLP

This Jupyter Notebook-based project demonstrates various Natural Language Processing (NLP) and data analysis techniques using Python. The project includes text analysis, sentiment analysis, named entity recognition (NER), word cloud generation, and topic modeling.

Language: Jupyter Notebook - Size: 1.29 MB - Last synced at: 2 days ago - Pushed at: almost 2 years ago - Stars: 3 - Forks: 0

shaadclt/Summarization-Agent-Reflection

This project uses LlamaIndex's Introspective Agent to summarize product specification documents with a focus on performance specs and safety features. The pipeline loads PDF documents, extracts text, and generates a summary in less than 50 words using a reflective agent loop.

Language: Jupyter Notebook - Size: 59.6 KB - Last synced at: 8 days ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/Heathcare-Assistant-Agent-ReAct

This project is an intelligent AI-powered Healthcare Assistant built using LlamaIndex, Groq’s blazing-fast LLMs (like llama-3-70b), and Wikipedia-based tools to answer medical questions about diseases, symptoms, and medications. It uses ReAct-style agent prompting to combine reasoning and tool use for reliable responses.

Language: Jupyter Notebook - Size: 29.3 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/Multi-Agent-Stock-Analysis

This project demonstrates a multi-agent system built using AutoGen and Groq's LLaMA 3 model, designed to automate the analysis of Apple (AAPL) stock's daily closing prices over the past month. The system utilizes a collaborative architecture involving multiple AI agents—each assigned a specific role in the data analysis pipeline.

Language: Jupyter Notebook - Size: 22.5 KB - Last synced at: about 2 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/Multi-Agent-Conversation-AutoGen

This project demonstrates a conversational AI simulation between a high school student and a math tutor using the AutoGen framework and the Groq API (with LLaMA 3 model). The use case focuses on helping students understand quadratic equations through a multi-turn dialogue.

Language: Jupyter Notebook - Size: 11.7 KB - Last synced at: 8 days ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/Customer-Service-AI-Agent-LlamaIndex

This project demonstrates how to build an intelligent customer support agent using LlamaIndex, Groq’s LLaMA 3.3 70B, and HuggingFace Embeddings. The agent can answer questions about orders, return policies, delivery dates, and customer support information by combining function-calling tools and a vector-based RAG setup.

Language: Jupyter Notebook - Size: 29.3 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/Routing-Agent-Llamaindex

This project demonstrates a routing agent setup using LlamaIndex, Groq's LLaMA3-70B model, and HuggingFace Embeddings for answering queries from multiple domain-specific documents.

Language: Jupyter Notebook - Size: 90.8 KB - Last synced at: 8 days ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/Supplier-Analysis-Smolagents

This project provides tools for analyzing ice cream supplier data, calculating transportation costs, tariffs, and total procurement expenses. It leverages the power of smolagents to create intelligent agents that can perform complex calculations and answer natural language queries about supplier data.

Language: Jupyter Notebook - Size: 28.3 KB - Last synced at: about 1 month ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/LangGraph-Summarizer-Agent

This project is a document summarization chatbot built with LangChain, LangGraph, Groq, and Huggingface embeddings, running in Google Colab. It can generate concise summaries from documents, take user feedback, and refine summaries through multiple review iterations.

Language: Jupyter Notebook - Size: 67.4 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/Orders-Chatbot-Custom-Agent-LangGraph

An Agentic chatbot built using LangChain, Groq Inference Engine (Llama3-70B), and LangGraph, that manages laptop product orders by interacting with structured tools. The agent can retrieve and update laptop order information from a CSV database, handle greetings, and small talk professionally.

Language: Jupyter Notebook - Size: 29.3 KB - Last synced at: 6 days ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/Product-QnA-Agentic-Chatbot

This project creates an intelligent product information chatbot that can answer questions about laptops sold by a company. It demonstrates the power of LLMs in creating interactive, context-aware agents that can retrieve and present information naturally.

Language: Jupyter Notebook - Size: 24.4 KB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 2 - Forks: 0

shaadclt/Zomato-Dataset-Analysis

This project involves the analysis of the Zomato dataset for restaurants in Bengaluru city. The dataset provides information about various restaurants, including their ratings, cuisines, costs, and more. Through this analysis, we aim to gain insights into the restaurant landscape in Bengaluru and explore factors that influence ratings.

Language: Jupyter Notebook - Size: 2.56 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 3 - Forks: 1

shaadclt/crewAI-Multi-AI-Agents-Investment-Risk-Analysis

This project automates the process of monitoring market data, developing trading strategies, executing trades, and assessing risks using a team of specialized AI Agents from crewAI. Each agent is equipped with specific roles and goals, and they collaborate to optimize trading decisions and strategies.

Language: Jupyter Notebook - Size: 105 KB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 7 - Forks: 1

shaadclt/Doctor-Assist-crewAI

This project leverages advanced AI agents from crewAI to assist doctors in diagnosing medical conditions and recommending treatment plans based on patient-reported symptoms and medical history. The solution uses Streamlit for the user interface and crewai library to define and manage AI agents and tasks.

Language: Python - Size: 25.4 KB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 8 - Forks: 1

shaadclt/Groq-Whisper-Transcription-App

A Streamlit-based web application that transcribes audio files using OpenAI's Whisper API. You can either upload an MP3 file or input a YouTube URL to convert video audio into text within seconds.

Language: Python - Size: 14.6 KB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 4 - Forks: 0

shaadclt/LLM-powered-PDF-Chatbot

This is a Streamlit-based PDF Chatbot powered by OpenAI's Language Models. The chatbot allows users to upload PDF files, extract text content, and ask natural language questions about the PDF content

Language: Python - Size: 12.7 KB - Last synced at: 4 months ago - Pushed at: over 1 year ago - Stars: 12 - Forks: 3

shaadclt/Conversational-Chatbot

This project is a Streamlit-based conversational chatbot that uses OpenAI's API to generate responses. The chatbot can transcribe audio input, generate text responses, and convert text responses back to audio.

Language: Python - Size: 20.5 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0

shaadclt/Image-based-Recipe-Retrieval-System

PalatePixels is a web application for recognizing Indian recipes from images and providing recipe details.

Language: Python - Size: 64.7 MB - Last synced at: 4 months ago - Pushed at: over 1 year ago - Stars: 4 - Forks: 0

shaadclt/Agent-Gauge

Agent Gauge is an AI AgentsOps monitoring library for Crew AI applications. It captures essential metrics such as token counts, costs, execution time, resource utilization, carbon emissions, and detailed logs. Additionally, it offers both textual and visual representations of the collected data via a Command-Line Interface (CLI) or Streamlit.

Language: Python - Size: 13.7 KB - Last synced at: 8 days ago - Pushed at: 5 months ago - Stars: 2 - Forks: 0

shaadclt/End-to-End-Text-Summarization-Project

This project implements an end-to-end text summarization pipeline using Natural Language Processing (NLP) techniques. The model is deployed using AWS EC2 and AWS ECR with CI/CD automation through GitHub Actions.

Language: Jupyter Notebook - Size: 68.4 KB - Last synced at: about 2 months ago - Pushed at: 6 months ago - Stars: 2 - Forks: 0

shaadclt/Cold-Email-Generator-Using-Job-URL

Cold Mail Generator is a Streamlit-based web application that automates the process of extracting job postings from career pages and generating personalized cold emails for job applications. The application leverages Llama 3.3 through Groq, LangChain and integrates with ChromaDB for portfolio link retrieval.

Language: Python - Size: 14.6 KB - Last synced at: 3 months ago - Pushed at: 6 months ago - Stars: 2 - Forks: 0

shaadclt/Multi-Agent-Financial-Analysis

This project utilizes a multi-agent system powered by crewAI to monitor, analyze, and strategize in the financial markets, specifically focusing on stock trading. Each agent in the system specializes in a unique aspect of trading, working together to provide comprehensive insights and actionable strategies.

Language: Jupyter Notebook - Size: 10.7 KB - Last synced at: about 2 months ago - Pushed at: 10 months ago - Stars: 4 - Forks: 0

shaadclt/Fine-tune-PaliGemma-Image-Captioning

This project demonstrates how to fine-tune PaliGemma model for image captioning. The PaliGemma model, developed by Google Research, is designed to handle images and generate corresponding captions.

Language: Jupyter Notebook - Size: 408 KB - Last synced at: 4 months ago - Pushed at: 8 months ago - Stars: 6 - Forks: 0

shaadclt/AI-Agents-CrewAI-Gemini

This repository contains a project that leverages AI agents using CrewAI and Google Gemini to research and write about the latest trends in AI technology, specifically focusing on healthcare.

Language: Python - Size: 14.6 KB - Last synced at: 4 months ago - Pushed at: about 1 year ago - Stars: 6 - Forks: 0

shaadclt/Heart-Disease-Prediction-KNN

This project focuses on predicting heart disease using the K-Nearest Neighbors (KNN) classification algorithm implemented in a Jupyter Notebook. It aims to provide a tool that can assist in early detection and diagnosis of heart disease based on given input features.

Language: Jupyter Notebook - Size: 301 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 5 - Forks: 0

shaadclt/Twitter-Hashtag-Analysis

This project provides a website that allows users to analyze real-time tweets from Twitter based on a specific hashtag. The website includes a tweet sentiment analyzer to determine the sentiment (positive, negative, or neutral) of the collected tweets.

Language: Python - Size: 114 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 7 - Forks: 1

shaadclt/Matplotlib-Exercises

This project provides a collection of Jupyter Notebook exercises for practicing Matplotlib plots, including bar plots, histograms, pie charts, and scatter plots. Matplotlib is a powerful data visualization library in Python that allows for creating a wide range of plots and visualizations.

Language: Jupyter Notebook - Size: 563 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 6 - Forks: 1

shaadclt/Multiple-Disease-Prediction-System

The Multiple Disease Prediction project aims to create a user-friendly web application that allows users to input relevant medical information and receive predictions for different diseases.

Language: Jupyter Notebook - Size: 95.7 KB - Last synced at: 4 months ago - Pushed at: over 1 year ago - Stars: 18 - Forks: 7

shaadclt/Sportsperson-Image-Classifier

This project is an image classifier that can identify different sportspersons using OpenCV, Haar cascades, and logistic regression. The classifier is deployed using Flask, allowing users to interact with it through a web interface.

Language: Jupyter Notebook - Size: 96.2 MB - Last synced at: 3 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Article-Research-Write-AI-Agents

This project sets up agentic automation for planning, writing, and editing articles using AI agents with crewAI.

Language: Jupyter Notebook - Size: 18.6 KB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 5 - Forks: 1

shaadclt/Model-Conversion-HuggingFace-GGUF

This project demonstrates how to download a model from Hugging Face, convert it to GGUF format, and upload it back to Hugging Face using a Colab notebook.

Language: Jupyter Notebook - Size: 30.3 KB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 5 - Forks: 1

shaadclt/Student-Performance-Analysis

This project involves the analysis of student performance using Seaborn plots in Jupyter Notebook. The dataset contains information about students' demographics, study habits, and performance in various subjects. Through this analysis, we aim to gain insights into the factors that influence student performance.

Language: Jupyter Notebook - Size: 476 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 5 - Forks: 0

shaadclt/Socratic-Learning-Assistant

This is an AI-powered learning assistant designed to help users explore and understand data structures (such as arrays, trees, graphs, and linked lists) using the Socratic method. Built using Streamlit and Google Generative AI (Gemini 1.5 Pro), the assistant guides learners by asking probing questions rather than providing direct answers.

Language: Python - Size: 10.7 KB - Last synced at: 23 days ago - Pushed at: 9 months ago - Stars: 3 - Forks: 0

shaadclt/CNN-Based-Anomaly-Detection-in-Time-Series-Data

This project demonstrates how to build a Convolutional Neural Network (CNN) model for anomaly detection in time series data using Keras. It is implemented in Google Colab and uses a CSV dataset containing time series values. The model detects anomalies based on reconstruction errors by setting a dynamic threshold.

Language: Jupyter Notebook - Size: 99.6 KB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 5 - Forks: 0

shaadclt/Youtube-Comments-Sentiment-Analysis-BERT

This project provides a sentiment analysis tool for YouTube comments using BERT (Bidirectional Encoder Representations from Transformers).

Language: Python - Size: 60.5 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Customer-Outreach-Campaign-crewAI

This repository demonstrates the use of CrewAI to enhance sales outreach and lead profiling using a combination of advanced AI agents and tools. The project leverages CrewAI agents and LangChain to identify high-value leads and craft personalized outreach campaigns.

Language: Jupyter Notebook - Size: 12.7 KB - Last synced at: 4 months ago - Pushed at: 10 months ago - Stars: 7 - Forks: 0

shaadclt/Translation-Chat-App-Qwen-2

This project is a Jupyter Notebook-based application that allows users to translate text into different languages (English, Chinese, and Japanese) or chat with an AI model. The notebook utilizes the Qwen/Qwen2-1.5B-Instruct language model for natural language processing tasks and the gTTS library for text-to-speech conversion.

Language: Jupyter Notebook - Size: 17.6 KB - Last synced at: 4 months ago - Pushed at: 11 months ago - Stars: 4 - Forks: 0

shaadclt/PDF-Data-Extraction-PyMuPDF4LLM

This repository demonstrates how to extract text, images, and structured content from PDF documents using pymupdf4llm in Google Colab. It also includes data preparation for LlamaIndex for further document analysis and information extraction.

Language: Jupyter Notebook - Size: 17.6 KB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 4 - Forks: 0

shaadclt/Vehicle-Tracking-Counting-YOLOv8

This Jupyter notebook project uses YOLOv8 for vehicle tracking and implements a line crossing detection algorithm. The system counts vehicles that cross a specified line in a video, annotates the frames, and generates an output video with visualizations.

Language: Jupyter Notebook - Size: 2.63 MB - Last synced at: 4 months ago - Pushed at: over 1 year ago - Stars: 4 - Forks: 0

shaadclt/shaadclt

Special Repository

Size: 90.8 KB - Last synced at: about 2 months ago - Pushed at: 9 months ago - Stars: 3 - Forks: 0

shaadclt/Home-Price-Prediction-Economic-Indicators

This project aims to predict home prices using various economic indicators from the Federal Reserve Economic Data (FRED). The project involves data collection, data preparation, model building, and analysis of the results.

Language: Jupyter Notebook - Size: 14.6 KB - Last synced at: about 2 months ago - Pushed at: 9 months ago - Stars: 3 - Forks: 0

shaadclt/Multi-Agent-Customer-Support-Automation

This project leverages the crewAI AI agents to create a sophisticated support system. These agents provide top-notch support and quality assurance for customer inquiries.

Language: Jupyter Notebook - Size: 14.6 KB - Last synced at: about 2 months ago - Pushed at: 9 months ago - Stars: 3 - Forks: 1

shaadclt/Customer-Segmentation-KMeansClustering

This project involves segmenting customers using k-means clustering in Jupyter Notebook. Customer segmentation is a powerful technique used in marketing and business analytics to divide customers into distinct groups based on their behaviors, preferences, or demographics.

Language: Jupyter Notebook - Size: 60.5 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 7 - Forks: 0

shaadclt/Conversation-Analysis-LangChain-Groq

This project utilizes the LangChain and Groq to perform various analyses on loan recovery conversations. The primary functionalities include summarizing conversations, identifying key actions or next steps, and undertaking sentiment analysis of both the recovery agent and the borrower.

Language: Jupyter Notebook - Size: 9.77 KB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 3 - Forks: 0

shaadclt/Product-Recommendation-System

This is a simple product recommendation system built using Python and Streamlit. The application provides product recommendations based on similarity scores and displays them in a visually appealing format.

Language: Python - Size: 1.06 MB - Last synced at: 4 months ago - Pushed at: 9 months ago - Stars: 3 - Forks: 0

shaadclt/Agentic-Automated-Event-Planning

This project demonstrates the use of CrewAI's multi-agent system to manage various aspects of event planning and execution.

Language: Jupyter Notebook - Size: 11.7 KB - Last synced at: 4 months ago - Pushed at: 10 months ago - Stars: 3 - Forks: 0

shaadclt/Data-Preprocessing-Pipeline

This project contains a data preprocessing pipeline implemented in Python using the pandas and numpy libraries. The pipeline handles missing values, outliers, and normalizes numeric features in a dataset.

Language: Jupyter Notebook - Size: 5.86 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Statistics-Python

This project provides a collection of Jupyter Notebook exercises for practicing statistics concepts using Python. Statistics is a fundamental field in data analysis and plays a crucial role in understanding and interpreting data. Through this project, we aim to enhance our statistical skills by implementing various concepts using Python.

Language: Jupyter Notebook - Size: 798 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Algorithmic-Trading-Python

This is a Python application that uses the Streamlit library to perform algorithmic trading analysis based on stock momentum. It retrieves stock data from Yahoo Finance using the yfinance library and visualizes the momentum and buying/selling signals using Plotly.

Language: Python - Size: 12.7 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Turbofan-Predictive-Maintenance

This repository contains code for a predictive maintenance project using machine learning. The goal of this project is to predict the Remaining Useful Life (RUL) of aircraft engines based on sensor data and other operational parameters.

Language: Jupyter Notebook - Size: 4.8 MB - Last synced at: 4 months ago - Pushed at: almost 2 years ago - Stars: 5 - Forks: 0

shaadclt/Ragas-Synthetic-Test-Data-Generation

This project demonstrates how to generate synthetic test data for Retrieval Augmented Generation (RAG) using Ragas.

Language: Jupyter Notebook - Size: 102 KB - Last synced at: 4 months ago - Pushed at: 12 months ago - Stars: 3 - Forks: 0

shaadclt/Ed-Tech-Company-QA-Assistant

This project is a QA (Question-Answering) assistant designed for an Ed-Tech company. It leverages vector databases, state-of-the-art language models, and custom document embeddings to provide accurate responses to user queries based on a pre-defined knowledge base.

Language: Python - Size: 29.3 KB - Last synced at: 4 months ago - Pushed at: 11 months ago - Stars: 3 - Forks: 0

shaadclt/Hybrid-Search-RAG-LangChain-Pinecone

This repository contains a Google Colab notebook that demonstrates how to set up and use a hybrid search Retrieval-Augmented Generation (RAG) system using LangChain and Pinecone. The hybrid search combines vector embeddings and sparse (BM25) encodings to provide efficient and accurate information retrieval.

Language: Jupyter Notebook - Size: 26.4 KB - Last synced at: 4 months ago - Pushed at: 10 months ago - Stars: 5 - Forks: 0

shaadclt/Debt-Recovery-Analysis-LangChain-Groq

This project leverages Langchain and Groq to analyze conversations between recovery agents and borrowers. The analysis includes summarization, key actions identification, sentiment analysis, named entity recognition (NER), and non-compliance checks.

Language: Jupyter Notebook - Size: 16.6 KB - Last synced at: 4 months ago - Pushed at: 10 months ago - Stars: 5 - Forks: 0

shaadclt/Image-Generation-App-DALL-E-Huggingface-Diffusers

This project is a Streamlit-based web app that enables users to generate AI-generated images using text prompts. The app integrates two powerful image generation models: OpenAI's DALL-E and Huggingface's Diffusion models.

Language: Python - Size: 10.7 KB - Last synced at: about 2 months ago - Pushed at: 9 months ago - Stars: 3 - Forks: 0

shaadclt/Retail-Store-Database-Assistant

This project is a Retail Store Database Assistant that uses LangChain and Google Palm Language Model to interact with a MySQL database. Users can ask questions about the database, and the assistant will generate MySQL queries to retrieve relevant information.

Language: Python - Size: 13.7 KB - Last synced at: 4 months ago - Pushed at: over 1 year ago - Stars: 5 - Forks: 0

shaadclt/Iris-Species-Detection-KNN

This project involves detecting iris species using the k-nearest neighbors (KNN) algorithm in Jupyter Notebook. The iris species detection task is a classic problem in machine learning, where the goal is to classify iris flowers into different species based on their measurements.

Language: Jupyter Notebook - Size: 43 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Fake-News-Detection-DecisionTreeClassifier

This project involves detecting fake news using a decision tree classifier in Jupyter Notebook. Fake news detection is an important task in the field of natural language processing and machine learning, as it helps identify and filter out misleading or false information.

Language: Jupyter Notebook - Size: 11.1 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Future-Sales-Prediction-LinearRegression

This repository provides a sales prediction model using linear regression for an advertising dataset. The model aims to predict sales based on various advertising channels, such as TV, radio, and newspaper.

Language: Jupyter Notebook - Size: 146 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Diabetic-Patient-Prediction

This project aims to predict diabetic patients using three different classification algorithms: Logistic Regression, Support Vector Classifier, and Random Forest Classifier. The project is implemented using Python and leverages scikit-learn, a popular machine learning library.

Language: Jupyter Notebook - Size: 1.15 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 5 - Forks: 0

shaadclt/Employee-Attrition-Dashboard-PowerBI

This project provides an interactive employee attrition dashboard created using Power BI. It aims to visualize and analyze employee attrition data to gain insights into factors contributing to employee turnover and develop strategies for retention.

Size: 434 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Chatbot

This is a simple chatbot implemented using Python and Streamlit. The chatbot uses a logistic regression classifier with TF-IDF vectorization to classify user input and generate appropriate responses.

Language: Python - Size: 14.6 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/Classification-AutoML-App

This is a sample application that demonstrates how to build a classification AutoML app using Streamlit, Pandas Profiling, and PyCaret.

Language: Python - Size: 5.86 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/Store-Data-Analysis-Excel

This project provides a guide for analyzing store data using Microsoft Excel. It demonstrates how to utilize various Excel features and functions to gain insights into sales, trends, and other key metrics related to store performance.

Size: 13.7 MB - Last synced at: about 2 hours ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/Hate-Speech-Detection

This project implements a hate speech detection model using a decision tree classifier and Twitter data.

Language: Python - Size: 1.12 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/Sarcasm-Detection

This is a web application built using Streamlit that performs sarcasm detection on input text.

Language: Python - Size: 1.78 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/Tech-Stocks-Performance-Analysis

This is a web application that allows you to analyze the performance of tech stocks. It retrieves stock data from Yahoo Finance using the yfinance library and visualizes the data using Plotly and Streamlit.

Language: Python - Size: 5.86 KB - Last synced at: 23 days ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/Time-Series-Analysis-Stocks

This is a Streamlit application that performs time series analysis on stocks. It allows users to input a stock ticker symbol and displays various visualizations for the selected stock.

Language: Python - Size: 5.86 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/Data-ETL-Pipeline

This code demonstrates how to load the Fashion MNIST dataset using TensorFlow's Keras API, preprocess the data, and store it in a SQLite database. The Fashion MNIST dataset consists of grayscale images of clothing items with corresponding labels.

Language: Jupyter Notebook - Size: 3.91 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/A-B-Testing-CaseStudy

This code performs an A/B testing analysis using control and test group data. It analyzes various metrics such as amount spent, number of impressions, reach, website clicks, searches received, content viewed, added to cart, and purchases. The analysis includes visualizations of the data using Plotly.

Language: Jupyter Notebook - Size: 1.26 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/Malaria-Detection-Tensorflow

A Flask web application for detecting malaria infection using a pre-trained VGG19 model.

Language: Jupyter Notebook - Size: 70.2 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Music-Store-Analysis-SQL

This repository contains a collection of SQL queries that can be used to extract information from a database. Each query is designed to solve a specific problem or retrieve specific data. The queries cover various scenarios, including finding the most senior employee, analyzing customer spending, determining popular genres, and more.

Size: 495 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/IPL-Win-Probability-Predictor

The IPL Win Probability Predictor is a web application built using Streamlit. It uses a machine learning model to predict the probability of a team winning an IPL match based on various factors such as batting team, bowling team, host city, target, score, overs completed, and wickets.

Language: Jupyter Notebook - Size: 1.71 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 5 - Forks: 0

shaadclt/Django-Clickkart-Ecommerce

This is an E-commerce website built using Django, a Python web framework. It provides a platform for users to browse and purchase products, while also offering various features for both users and administrators.

Language: CSS - Size: 24.9 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Instagram-Static-Website

This project is a replica of the Instagram homepage, created using HTML and CSS. It provides a static representation of the layout and design of the Instagram login page, including the logo, input fields, buttons, and footer.

Language: HTML - Size: 575 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 1

shaadclt/Netflix-Data-Analysis-Tableau

This project explores the Netflix dataset using Tableau, a powerful data visualization tool. It aims to analyze and visualize various aspects of Netflix's content catalog and provide insights into the streaming platform.

Size: 2.05 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 0

shaadclt/Responsive-Website-Kawa-Space

This project aims to recreate the responsive design of the Kawa Space website.

Language: HTML - Size: 1.14 MB - Last synced at: 29 days ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Hotel-Booking-Analysis-Python

This project provides an analysis of hotel booking cancellations using Python. It aims to uncover patterns and insights related to hotel booking cancellations and understand the factors that contribute to cancellations in the hospitality industry.

Language: Jupyter Notebook - Size: 2.73 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 2 - Forks: 1

shaadclt/Employee-Salary-Prediction-DecisionTreeClassifier

This project aims to predict the salary of employees based on various features using a decision tree classifier algorithm. By analyzing the provided dataset, the model can make accurate predictions if the salaries of new employees is above 100K or not.

Language: Jupyter Notebook - Size: 7.81 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 1

shaadclt/Digits-Classification-RandomForestClassifier

This project aims to classify handwritten digits using a random forest classifier algorithm. By analyzing the provided dataset of handwritten digits, the model can accurately predict the digit represented in the image.

Language: Jupyter Notebook - Size: 20.5 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Movie-Correlation-Analysis

This repository provides a movie correlation analysis using Python. The analysis aims to explore the relationships and correlations between different movie attributes, such as ratings, genres, and revenue.

Language: Jupyter Notebook - Size: 650 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Cancer-Classification-SupportVectorClassifier

This repository provides a cancer classification model using Support Vector Classifier (SVC). The model aims to classify cancer cases into benign or malignant based on various features obtained from medical examinations.

Language: Jupyter Notebook - Size: 14.6 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Django-Signup-Adminpanel

This Django project implements an authentication system with user registration, login, logout, and admin functionalities.

Language: HTML - Size: 33.2 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Password-Strength-Checker-RandomForestClassifier

This project is a password strength checker that utilizes a Random Forest Classifier to determine the strength of a given password. The Random Forest Classifier is trained on a dataset of passwords labeled with their corresponding strength levels.

Language: Jupyter Notebook - Size: 5.03 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Spotify-Dataset-EDA

This project is an Exploratory Data Analysis (EDA) on the Spotify dataset. The dataset contains information about various songs, including their features such as danceability, energy, loudness, and more. Through this analysis, we aim to gain insights into the characteristics of the songs and explore any patterns or trends.

Language: Jupyter Notebook - Size: 696 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Energy-Output-Prediction-MultipleLinearRegressor

This project involves the prediction of energy output in a Combined Cycle Power Plant (CCPP) using Multiple Linear Regression in Jupyter Notebook. The dataset contains features such as temperature, pressure, humidity, and exhaust vacuum, which are used to predict the net hourly electrical energy output.

Language: Jupyter Notebook - Size: 1.84 MB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/House-Price-Prediction-DecisionTreeRegressor

This project involves the prediction of house prices in Bengaluru city using Decision Tree Regression in Jupyter Notebook. Through this analysis, we aim to build a regression model that accurately predicts house prices based on the given input features.

Language: Jupyter Notebook - Size: 144 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Boston-House-Price-Prediction-LassoRegression

This project involves the prediction of house prices in Boston using Lasso Regression in Jupyter Notebook. The dataset contains features such as average number of rooms per dwelling, crime rate, and more. Through this analysis, we aim to build a regression model that accurately predicts house prices based on the given input features.

Language: Jupyter Notebook - Size: 9.77 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Salary-Prediction-SupportVectorRegressor

This project involves the prediction of salary based on position using Support Vector Regression (SVR) in Jupyter Notebook. The dataset contains information about different positions and their corresponding salaries. Through this analysis, we aim to build a regression model that accurately predicts the salary based on the given position.

Language: Jupyter Notebook - Size: 27.3 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Diabetes-Progression-Prediction-RidgeRegression

This project involves the prediction of diabetes progression using Ridge Regression in Jupyter Notebook. The dataset contains features such as glucose level, blood pressure, body mass index, and more. Through this analysis, we aim to build a regression model that accurately predicts the progression of diabetes based on the given input features.

Language: Jupyter Notebook - Size: 8.79 KB - Last synced at: 17 days ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Kozhikode-Pollution-Analysis

This project involves the analysis of pollution data in Kozhikode city, where the data is acquired using an API and visualized using Matplotlib in Jupyter Notebook. The project aims to gain insights into the pollution levels during a week and visualize the trends and patterns.

Language: Jupyter Notebook - Size: 11.7 KB - Last synced at: 7 days ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Feature-Selection-Techniques

This project involves the implementation of different feature selection techniques in Jupyter Notebook for practice. Feature selection is an important step in machine learning that aims to select the most relevant features from a given dataset. Through this project, we aim to explore and understand various feature selection techniques.

Language: Jupyter Notebook - Size: 156 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Feature-Engineering-Techniques

This project involves the implementation of different feature engineering techniques in Jupyter Notebook for practice. Feature engineering is a crucial step in machine learning that involves transforming raw data into meaningful features to improve model performance. Through this project, we aim to practice various feature engineering techniques.

Language: Jupyter Notebook - Size: 1020 KB - Last synced at: about 1 month ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/Seaborn-Exercises

This project provides a collection of Seaborn exercise plots implemented in Jupyter Notebook for practice. Seaborn is a powerful data visualization library in Python that offers a variety of statistical plots and visualization techniques. Through this project, we aim to enhance our skills in data visualization using Seaborn.

Language: Jupyter Notebook - Size: 402 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 3 - Forks: 0

shaadclt/NumPy-Exercises

This project provides a collection of Jupyter Notebook exercises for practicing NumPy, a fundamental library for numerical computing in Python. NumPy provides powerful data structures and functions for handling large, multi-dimensional arrays and matrices. Through this project, we aim to enhance our skills in NumPy.

Language: Jupyter Notebook - Size: 5.86 KB - Last synced at: 4 months ago - Pushed at: about 2 years ago - Stars: 4 - Forks: 0

shaadclt/Scikit-learn-Exercises

This project provides a collection of Jupyter Notebook exercises for practicing scikit-learn, a popular machine learning library in Python. Scikit-learn provides a wide range of machine learning algorithms, tools for data preprocessing, model evaluation, and more. Through this project, we aim to enhance our skills in Scikit-learn.

Language: Jupyter Notebook - Size: 205 KB - Last synced at: about 1 month ago - Pushed at: about 2 years ago - Stars: 6 - Forks: 0