Minimalist Data Wrangling with Python (Open-Access Textbook)

Stats, linear algebra and einops for xarray

Undergraduate thesis, Seoul National University Dept. of Economics — "Modeling Volatility and Risk Spillover Between the Financial Markets of US and China Using GARCH Value-at-Risk Forecasting and Granger Causality."

Predicting how much loan will be approved

This repo contains projects, tasks and other code which I have developed on a Data Scientist course at SkillFactory.

HISDAC-ES: Creating historical settlement data for Spain (1900-2020) based on cadastral building footprint data

https://gulinan.github.io/mat244e/

Comparison of A/B Test and Conversion of Bidding Methods

A F&B manager wants to determine whether there is any significant difference in the diameter of the cutlet between two units. A randomly selected sample of cutlets was collected from both units and measured? Analyze the data and draw inferences at 5% significance level. Please state the assumptions and tests that you carried out to check validit…

NU Bootcamp Project 1 (Modules 7 & 8)

Rating Product & Sorting Reviews in Amazon

This is QA-Stocks, an app that tries to predict stocks using SciPy!

Data-oriented Python course taught for all Mercado Libre verticals

This repository is about Data analysis with Python using libraries such as Pandas, Matplotlib, Seaborn, and NumPy to analysis prices of properties in given areas to predict future prices.

Mini-projects

Data Analysis, training Machine Learning models, and Model Evaluation and Refinement for LaptopPricing dataset.

The objective is to build a ML-based solution (linear regression model) to develop a dynamic pricing strategy for used and refurbished smartphones, identifying factors that significantly influence it.

python code for extracting data from csv file , using Matlab plot and seaborn Libraries

Data Analysis, training Machine Learning models, and Model Evaluation and Refinement for AutoMobiles dataset.

Assignment 2 Set 2