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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.
Automobile Data Insights: A data analysis project exploring trends in vehicle prices, fuel efficiency, and other key attributes. Uses Python, Pandas, Matplotlib, and Seaborn for data visualization and insights.
Welcome to my project. OpenPyVision is a real time videoMixer based on opencv and pyqt6.
A collection of Python libraries for data analysis and visualization, including NumPy, Pandas, Matplotlib, and Seaborn.
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.
A structured collection of Jupyter notebooks exploring NumPy from the ground up; covering array creation, manipulation, broadcasting, indexing, and data visualization for scientific computing and data analysis.
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.
Showing my daily progress in understanding machine learning.
The TARDIS Train Dashboard is a data analysis and visualization tool designed to process, clean, and analyze train delay data. It provides insights into train schedules, delays, and their causes, and offers predictive modeling for future delays.
13 Data Analysis Examples - MovieLens 25M Dataset
NumPy (short for Numerical Python) is a powerful Python library used for working with arrays, matrices, and numerical computations.
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.
This repository contains a Jupyter/Colab notebook `g_numpy.ipynb` where I have learned the **fundamentals of NumPy**, the core library for numerical computing in Python. It covers array creation, operations, and important techniques used in data science and scientific computing.
small pieces of Python code
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 consist sample programs to learn and understand core concepts
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