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Victor Lavado's Projects

abalone_pca_pipeline icon abalone_pca_pipeline

Set of different approaches to predict years of abalones using Principal Component Analysis (PCA) manually and as a hyper parameter tunning inside a pipeline

deployment_ml_classifier icon deployment_ml_classifier

This repository covers from scratch all the stages involved in the deployment of ML model from research/prototype enviroment to development and finally production.

optim_logit_model icon optim_logit_model

Implementation of an binary classification optimization model solved from logit perspective in a jupyter notebook using python and Scipy.optimize library

pybookmanager icon pybookmanager

Graphical User Interface (GUI) based on Python and SQL (sqlite3) that allows to manage a database of books and perfom operations such as view, add, delete and update books

pybookmanager-oop- icon pybookmanager-oop-

Graphical User Interface (GUI) based on Python and SQL (sqlite3) that allows to manage a database of books and perfom operations such as view, add, delete and update books. This version uses OOP instead of function-based code

pydic icon pydic

Dictionary that uses .json as a database for defintions of the inputs

pygeocode icon pygeocode

Program that imports csv file to a data frame using pandas library and then applies geocode to know the location of the address

pymysql icon pymysql

Script that uses Mysql database thorough mysql.connector library to look for words and return its defintion from a dictionary

pypossqlcollector icon pypossqlcollector

Web based app that sends your weight and weight average from a database to your email address

pypostgresql icon pypostgresql

Scrip that exectures some basic function in a PostreSQL usign Python code and Psycopg2 library

pysqlite3 icon pysqlite3

Some functions in sqlite 3 library (built-in python)

pywebmap icon pywebmap

Browser webmap made of custom layers and base map

pywebscrappingrealestate icon pywebscrappingrealestate

Python script that grabs data from a real estate webpage and generates a pandas dataframe and an csv file to allow for further analysis of realestate market

rf_drop_cat_var icon rf_drop_cat_var

Scrip that generates a dataframe from a given csv file (downloaded from Kaggle) to predict house prices in Melbourne by using a Random Forest Model. Data cleaning is done by droping columns with text elements.

trading icon trading

Leverage software to support trading and investment decision making

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