Perform the financial risk analysis on a stocks portfolio, through Monte Carlo Simulation

Examples about Data Science Packages

how to perform t-testing & ANOVA

This is my submission to be part of TusDatos

First project implementing Logistic Regression

Оптимизация производственных расходов металлургического комбината ООО «Так закаляем сталь».

Built a linear regression model to predict shared bike demand post-quarantine. Identified key variables affecting revenue and assessed model accuracy in describing bike demand.

Data Science: analytics for health and medicine WHO

The Bike-Sharing Demand Prediction Project aims to develop a predictive model to estimate the demand for shared bikes in the American market for BoomBikes, a bike-sharing provider looking to accelerate revenue post the Covid-19 pandemic. The project involves thorough data exploration and preprocessing.

OpenClassrooms Data Analyst 2022-2023 - Projet 6

O Statsmodels é uma biblioteca em Python dedicada à estimação e teste de modelos estatísticos. Ele fornece ferramentas para realizar análises estatísticas detalhadas, como regressão linear, modelos de séries temporais, análise de variância e testes estatísticos.

Working with consumer data to build a binary logistic machine that predicts the probability of purchasing from the catalog. Training that machine using an estimation sample, then testing and validating the machine using a holdout sample. I also analyze the mailing strategy we should use to achieve profits.

Currency Exchange Rate Forecasting is a Time-Series forecasting model which is built to forecast the INR-USD Currency Exchange Rates using SARIMAX algorithm.

Data Science Project: To predict which factors leads to churn and find customers who are likely to churn.

Analysing Time series and spatiotemporal data

Predict a price of 1BDR apartment in New York City based on Trulia, Yelp and demographic data.

Example for studying statsmodels

A simple linear regression machine learning model for predicting the total cases of pandemic from OWID dataset. Built using Python libraries (Pandas, NumPy, Statsmodels, Pickle, Matplotlib, Seaborn). Model is further represented as a Flask Web Application with a backend database connectivity to SQLite3 using SQLAlchemy. Later deployed to Heroku …

Time Series concepts and code snippets.