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api-rest-flask_restful

REST API build with flask_restful and JSON Web Token (JWT)

applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

awesome-cheatsheets

👩‍💻👨‍💻 Awesome cheatsheets for popular programming languages, frameworks and development tools. They include everything you should know in one single file.

azuredatabricks

Code and shared files

backend-django

Proyecto clon de instagram en Django

colabtools

Python libraries for Google Colaboratory

colombia_mapa

Divisiones políticas de departamentos y municipios en Colombia en formato topojson y geojson

danpeco.github.io

data-cleaning-rmotr-freecodecamp

datapipelines-essentials-python

Simplified ETL process in Hadoop using Apache Spark. Has complete ETL pipeline for datalake. SparkSession extensions, DataFrame validation, Column extensions, SQL functions, and DataFrame transformations

deeplearningpython

neuralnetworksanddeeplearning.com integrated scripts for Python 3.5.2 and Theano with CUDA support

deltalake

This repository contains the notebooks and presentations we use for our Databricks Tech Talks

django_instagram

Instagram type web app

django_web_application

Blog type Web Application with Django

dsgo-dl-workshop-summer-2020

Deep Learning Workshop for Data Science Go Virtual Event Summer 2020

flask_web_appplication

Full feature blog style web application with Flask in Python

freecodecamp-intro-to-pandas

freecodecamp-pandas-real-life-example

maze_generator

Random maze generator and solver

ml001-project-sources-code-and-learning-materials

ML001 Sources Code and Learning Materials

modelo-accidentes

Estes es un proyecto donde realizamos analisis de datos y algoritmo predictivos sobre los dataset de accidentalidad de la ciudad de Medellin durante el periodo 2019

neural-networks-and-deep-learning

Code samples for my book "Neural Networks and Deep Learning"

pandas-videos

Jupyter notebook and datasets from the pandas Q&A video series

pyspark-example-project

Implementing best practices for PySpark ETL jobs and applications.

rdp-reading-data-with-python-and-pandas

snakeai

t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

tensorflow-2.0-keras

TensorFlow 2.0 + Keras guide by François Chollet for deep learning researchers.

webscrapping

whr-eda-clustering

Exploratory Data Analysis of World Happiness Report and K-means Clustering