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projeto-frontend-html-css

FRONT END - Criação de mais de uma pagina web com redirecionamento de links de uma pagina a outra.

python-basics-exercises

Python Basics: A Practical Introduction to Python 3

pythonmikkeli

Data Science Course Materials for Aalto University in Mikkeli

python_and_the_web

Build Bots, Scrape a website or use an API to solve a problem.

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch

pytorch-semseg

Semantic Segmentation Architectures Implemented in PyTorch

pytorch_experiments

Auto Encoders in PyTorch

rake-nltk

readme-template

README.md template for your open-source project

references

road-semantic-segmentation

Udacity Self-Driving Car Engineer Nanodegree. Project: Road Semantic Segmentation

semantic-segmentation

Improving Semantic Segmentation via Video Propagation and Label Relaxation

senegal-national-assembly

sentence-vae

PyTorch Re-Implementation of "Generating Sentences from a Continuous Space" by Bowman et al 2015 https://arxiv.org/abs/1511.06349

sms-spam-detection

SMS spam detection by using the Naive Bayes.

snorkel-tutorials

A collection of tutorials for Snorkel

stage3a

streamlit-example

Example Streamlit app that you can fork to test out share.streamlit.io

streamlit_bertopic

A simple web app for topic modelling

student-performance

Prediction of Student's performance based on social and demographic features.

students-academic-performance-dataset-xapi-edu-data-

studygroup

Welcome to the University of Toronto Coders!

team-members-section

Team members section for your website. Initially hide the description/overview of the team members and only display the description/overview about the specific team member once someone click on a specific team member's profile photo or name. Very light weight, fast loading and responsive web page for team members section. Easily convert it as WordPress template or create a new Custom Post Type so you can add team members very easily from your WordPress Dashboard.

test

testrepo.github.io

tf_idf_tutorial

For building any natural language models, the key challenge is how to convert the text data into numerical data. As the machine learning or deep learning models don’t understand the text data.Here we work with the TF-IDF method which is short for “term frequency–inverse document frequency”. This TF-IDF method is the popular word embedding technique used in various natural language process tasks.

titanic-eda

Exploratory Data analysis of the Titanic disaster dataset

vae

Example of vanilla VAE for face image generation at resolution 128x128 using pytorch.

variational-autoencoder-pytorch

Variational Autoencoder implemented with PyTorch, Trained over CelebA Dataset

wine

wine prediction dataset