YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

Open Source Computer Vision Library

Predict, Manage and Monitor the call drops of cell towers using Cloud Pak for Data

A collection of application which are built on open source technologies/frameworks like R Shiny, Plotly-Dash, Flask and Streamlit

Analysis of the call quality dataset found on data.gov.in for CS F415: Data Mining

code for DataCamp classes

Analyse customer segmentation, sentiment on product review, and built a product recommender system

Call Drop Prediction analysis on MyCall dataset. Predicted the category of call based on user inputs.

This project revolves around employing an LSTM model to forecast average network traffic. The implementation involves integrating the LSTM model within a Flask framework for deployment.

This repository contains dataset for different telecom operators, It contains the features like Network Type, Call Drop Category, In Out Travelling, Latitude, Longitude, State Names, Average Data U…

World Internet Connection Analysis

Practical projects showing my capabilities.

Develop an overview dashboard for managers utilizing a telecom industry user churn dataset to present insights on the current churn situation.

This project demonstrates the use of an artificial neural network to predict customer churn in a telecom company's customer base.

This repository is created to share the steps that were taken in making my Graduation Thesis for my Applied Statistics Diploma, the project is about creating a machine learning model to predict the…

Predictive analysis on Telco Churn using various ML algorithms

Seamlessly integrate LLMs into scikit-learn.

The Customer Churn table contains information on all 7,043 customers from a Telecommunications company in California in Q2 2022. We need to predict whether the customer will churn, stay or join the…

Learn how to build and deploy NLP model with FastAPI

Predictability classes for forecasting bank clients behavior by transactional data.

Dynamic classifier for estimating the predictability of client's transactional behaviour

A data science project to predict whether a transaction is a fraud or not.

Reproducible Machine Learning for Credit Card Fraud Detection - Practical Handbook

Private chat with local GPT with document, images, video, etc. 100% private, Apache 2.0. Supports oLLaMa, Mixtral, llama.cpp, and more. Demo: https://gpt.h2o.ai/ https://gpt-docs.h2o.ai/

Synthetic Credit Card Transaction Generator used in the Sparkov program.

Streamlit — A faster way to build and share data apps.

The home base for all my projects, code, analytics, visualizations, and tips.

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

Code for the paper "Benchmarking sentiment analysis methods for large-scale texts: A case for using continuum-scored words and word shift graphs"