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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!

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.

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%.

Repositório com exercícios básicos de Numpy para praticar.

Project on exploring optimization of quality delivery service using Python

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.

The objective of this project is to examine a user's screen usage through Python, with a focus on identifying the applications and websites they utilize and the duration of usage. The project employs a range of libraries including pandas, numpy, plotly.express, and plotly.graph_objects for data processing, visualization, and analysis purposes.

Pokemon Exploratory Data Analysis

Sauti East Africa request for a segmentation analysis on all of their user's behavior. Sauti wishes to better optimize their menu design and explore the feasibility of smart menus based on user predicted behavior.

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.