Udacity Data Analyst Nanodegree - Project III

A trading algorithm that identifies stocks with the largest potential for growth while heavily considering its volatility using quantopian

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.

A regression based modeling project to forecast the sales of Walmart

Modelo de pricing actuarial frecuencia-severidad (GLM Poisson × GLM Gamma) con scoring comercial XGBoost sobre el dataset freMTPL2 — 678.000 pólizas de seguro automotor francés.

Linear Regression model for a US bike-sharing provider BoomBikes

A/B tests are very commonly performed by data analysts and data scientists. It is important that you get some practice working with the difficulties of these.

My notes in Jupyter Notebooks for statistics, probability, and plotting applied with major python libraries as an introduction to machine learning.

Random Good Data Science Stuff

in this repository i will upload all the projects which i would make regarding deep learing. i will upload as much neural networks as possible.

An implementation of an ARIMA time series forecast using Python statsmodels and scipy.

Our group chose this question to bring attention to the little knowledge that young loan applicants have. Based on our findings in our models we explore: Which age group is the least likely to apply for loans? Which group is most likely to default on loans?

A predictive machine learning model to forecast the Algerian Forest Fire FWI using Python, Scikit-learn, and Statsmodels. Includes complete data cleaning and EDA.

Linear Regression Bike sharing Assignment

I perform a retrospective analysis on the linear regression analysis that I previously performed on the NYC Bike Counts dataset. Specifically, I analyze my linear regression analysis to identify anything that I could have done differently.

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Time Series Analysis

Assignment-04-Simple-Linear-Regression-1 Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regression.

ARIMA baseline forecasting on AMZN daily log returns with a reproducible pipeline (local mode + BigQuery feature store + SQL window functions) and an auto-generated report.

Model to identify the potential lead by assigning a score for their rate of conversion. Therefore, reaching out to potential is no more a brainstorming task.

A data analytics project that utilizes PANDAS, Numpy, Matplotlib and statsmodel to analyze the results of hypothesis testing and regression modeling in determining whether a website update should be launched.

End-to-end pairs-trading research framework: data acquisition, cointegration-based pair selection, vectorized backtests, analytics, and publication-ready figures (Python 3.10+).

It predicts the next price movements based on the given period(1hr,4hr....). Using the real time market price movements data from YahooFinance. And it also depicts the risk metrics. Visualizing the price history.

Analyze online shoppers' purchase intentions using Logistic Regression, K-means clustering & A/B Testing

Data Science: Storytelling and Deployment - analyzing LEGO Database with Streamlit.

Q1) Delivery_time -> Predict delivery time using sorting time. Build a simple linear regression model by performing EDA and do necessary transformations and select the best model using R or Python. EDA and Data Visualization, Feature Engineering, Correlation Analysis, Model Building, Model Testing and Model Predictions using simple linear regressi

Human Data Science Course Project A.Y. 2022/2023 @ Alma Mater Studiorum University of Bologna - UNIBO

Time-Based Analysis projects using pandas, scikit-learn and statsmodel.tsa

This repository describes the implementation of Machine Learning techinques using the Statsmodels pacakge

This dataset provided by Udacity in their data analyst course proivdes a walkthrough of an AB test for customer conversion.