Notebooks from Operação Serenata de Amor | ** Este repositório não recebe atualizações frequentes **

Taller SparkR para las Jornadas de Usuarios de R

Notes for in-depth learning of basic concepts in python programming.

LSTM based model for Named Entity Recognition Task using pytorch and GloVe embeddings

collection of numerical optimization methods

Self-Paced Learning Sandbox for Python with Virtual Environments, Tkinter, Turtle Graphics, Flask, Jupyter Notebooks, HTML & CSS

爬取当当网数据，并利用pyecharts进行可视化

Multilingual and Cross-Modal Embedded Representation for Tweets Aggregation

青空文庫のデータで、ニューラルネットを使って作者推定

PCEO Matemáticas e Ingeniería Informática

Processing Data from the TASS (Russian News Agency, https://tass.ru/ ). This is a personal project to practice in data processing. The main goal was to visually represent a timeline of COVID-19 related articles. Check the README.md for more

Example 4 from the python section of my webpage www.tom-p-data-science.com

Example 2 from the python section of my webpage www.tom-p-data-science.com

Example 2 from the python section of my webpage www.tom-p-data-science.com

This project implements various machine learning models to detect fraudulent credit card transactions.

sql example 1 - This is a basic example that shows how to use mysql.connector to connect to your database and create a table. In this example we create a table named "person" with two columns: Name and Last Name. The Name is chosen to be char (strange assumption just for this example) so a fixed-length string and Last Name is chose to be varchar…

Repo for projects from Udacity's Deep Learning Foundations

Example 1 from the python section of my webpage www.tom-p-data-science.com

The project involves performing sentiment analysis on the reviews referring to the most talked about features of the phone.The reviews are scraped using python from amazon.Topic modelling is used to obtain the four most talked about features of the phone. Sentiment Analysis is performed on the reviews related to these features.Each of the review…