M

matplotlib

Practical tasks on Deep Learning (DL) and Neural Networks (NN). 🤖

A practical, linear-algebra-first introduction to data science.

Analysis of Kilter Board data, along with predictive models for V-grades based on holds and angle.

Analysis of Tension Board 2 data, along with predictive models for V-grades based on holds and angle.

Python mathplotlib graphs of web articles. Contains plots of basic article characteristics over time.

Performed Exploratory Data Analysis (EDA) on the Google Play Store dataset using Python. Leveraged pandas for data cleaning and matplotlib for visualizations to analyze categories, ratings, installs, pricing, and update frequency. Created clear charts and dashboard-style visuals to uncover trends driving app popularity and user satisfaction.

Praktisi Mengajar Teknik Informatika Universitas Nusa Putra 2024

This project focuses on extracting and visualizing stock data using Python libraries such as yfinance for historical stock prices and web scraping techniques to gather company revenue data. It provides a comprehensive analysis by plotting both stock prices and revenues over time for companies like Tesla and GameStop.

This project predicts house prices using machine learning models based on the King County House Sales dataset. It explores Simple Linear, Multiple Linear, Polynomial, and Ridge Regression models, comparing their performance in terms of accuracy. The best model identified is Polynomial Regression, achieving an R² score of 0.75.

A library to help us make waterfall plots.

Creation of a trading robot for data analysis and manipulation of the libraries Pandas, Numby, MatplotLib, Yfinance, Seaborn

My approach on solving mathemetical modeling labs (university course)

Code from mechanic physics labs (university course)

My attempts to solve homework from the Moscow Institute of Physics and Technology course

All left code from labs 1-3 years(university studing)

Raw project code to complete labs of statistical radiophysics (university course)

Collection of completed data-mining (university course) on python

Simple raw code templates that used for create real size plots for semiconductor labs (university course)

Final project of course ML junior by Skillbox. Goal: Build model to predict client's loan default. Metrics: ROC-AUC

Project to evaluate the results and performance of the clustering and rescheduling algorithms for the Social Internet of Energy. Related scientific manuscripts: https://ieeexplore.ieee.org/abstract/document/8784194 https://www.mdpi.com/1424-8220/20/13/3704