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Python Basics, Machine Learning and Deep Learning

We implemented two Centralized approaches- NMPC and Velocity Obstacle Algorithm, along with two DeCentralized approaches- Priority Safe Interval Path Planning (SIPP), and Conflict Based Search (CBS) planning.

Welcome to my project. OpenPyVision is a real time videoMixer based on opencv and pyqt6.

This project was done in association with the Solar-Terrestrial Research Department(CSTR) in the New Jersey Institute of Technology (NJIT) and was purposely crafted to find the phenomenon STEVE.

Numpy ( Numerical Python ) Python Package.

Analyzing the customer dataset and developing a machine learning solution to segment customers into meaningful groups based on their purchasing behavior, demographics, and interaction with past marketing campaigns.

13 Data Analysis Examples - MovieLens 25M Dataset

A journey through 100 Days of Python, featuring multiple projects and games. Each day brings new coding challenges and fun, building skills and habits for consistent Python practice!

Crafted a Currency Convert, an intuitive currency converter that effortlessly integrates real-time exchange rates, delivering precise and up-to-date calculations and by integrating Python's inbuilt functions and leveraging libraries like NumPy and cutting the code complexity by 50%.

This repository is not just a collection of tutorials and practice exercises, but also a showcase of innovative projects that highlight the incredible potential of NUMPY in various fields.

Project on exploring optimization of quality delivery service using Python

Repositório com exercícios básicos de Numpy para praticar.

Computer vision program written in Python that uses OpenCV to automatically take pictures of people when they are smiling and have their eyes open. WIP.

A comprehensive guide to mastering NumPy with practical examples and applications in machine learning. Perfect for learners and developers looking to deepen their knowledge of numerical computations in Python.

Pokemon Exploratory Data Analysis

Conducted sentiment analysis and data visualization on YouTube comments using the TextBlob library, uncovering insights on audience engagement, emoji usage, and video performance metrics. Implemented linear regression models to explore correlations between views, likes, video titles, and audience engagement.

Here I analysed data and made pipeline out of it making model making/training/testing/selecting and hyperparameters selecting more user friendly and visualised, like an application. I have worked for this project ~2 weeks.

This repository consist sample programs to learn and understand core concepts