Explore something new
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Updated
Aug 31, 2023 - Python
Explore something new
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.
Numpy ( Numerical Python ) Python Package.
13 Data Analysis Examples - MovieLens 25M Dataset
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.
The Data Analysis Tool is a Python program that provides basic data analysis features for a given dataset.
Решение инженерных и экономических задач с NumPy
Explore AI algorithms (A*, K-means, Regression, KNN) in Python assigned by University-United International. Master diverse techniques in this educational code collection. 🤖🔍📊
Pokemon Exploratory Data Analysis
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.
MNIST handwritten digit classification
NumPy (short for Numerical Python) is a powerful Python library used for working with arrays, matrices, and numerical computations.
Data analysis of Instacart's grocery basket and customer profiling with evaluation of their shopping habits. (Career Foundry - Data Analytics project)
A supervised Learning model that finds out donors who earn more than $50K annually
This repository contains a case study for Google's Data Analytics Professional Certificate, focusing on Cyclistic, a fictional bike sharing company in Chicago. The case study aims to drive growth by converting casual riders into members through a marketing strategy.
Python Project which was aimed at data wrangling, analyzing and creating visualizations using python in Jupyter notbook .
The project focuses on predicting the presence of heart disease based on various medical variables such as age, sex, and cholesterol level. Decision tree models are employed for this classification task, exploring both basic and hyperparameter-tuned versions.
A few models were developed based on Decision trees and Logistic Regression to categorize fraudulent transactions
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