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How to use the DockerOperator in Airflow within Docker Compose?
How to deploy airflow on Kubernetes
Running Airflow inside Kubernetes
Cloudbox Labs blog code
Cloud ML Engine is now a part of AI Platform
Curso de Ciencia de datos
O'Reilly Book: [Data Algorithms with Spark] by Mahmoud Parsian
Developed a data pipeline to automate data warehouse ETL by building custom airflow operators that handle the extraction, transformation, validation and loading of data from S3 -> Redshift -> S3
Code for Data Pipelines with Apache Airflow
Data Visualization with Python
A repository to keep track of all the code that I end up writing for my blog posts.
Platzi Course about Data Engineering
Deep Learning Specialization courses by Andrew Ng, deeplearning.ai
Developing deep learning models using Pytorch
Repositorio del curso de Deep Learning con Pytorch de Platzi
Docker workshop
Python Data Science and Machine Learning for Beginners
Ejercicios y ejemplos utilizados en el libro Érase una vez Kubernetes
Explaining Anomalies Detected by Autoencoders Using SHAP
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Notebooks del curso de machine learning aplicado con python de platzi
Play with neural networks!
BEST SCORE ON KAGGLE SO FAR , EVEN BETTER THAN THE KAGGLE TEAM MEMBER WHO DID BEST SO FAR. The project is about diagnosing pneumonia from XRay images of lungs of a person using self laid convolutional neural network and tranfer learning via inceptionV3. The images were of size greater than 1000 pixels per dimension and the total dataset was tagged large and had a space of 1GB+ . My work includes self laid neural network which was repeatedly tuned for one of the best hyperparameters and used variety of utility function of keras like callbacks for learning rate and checkpointing. Could have augmented the image data for even better modelling but was short of RAM on kaggle kernel. Other metrics like precision , recall and f1 score using confusion matrix were taken off special care. The other part included a brief introduction of transfer learning via InceptionV3 and was tuned entirely rather than partially after loading the inceptionv3 weights for the maximum achieved accuracy on kaggle till date. This achieved even a higher precision than before.
poc pull request
PySpark Cheat Sheet - example code to help you learn PySpark and develop apps faster
Curso de Introducción a Machine Learning con Python
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.