Reac92

Mathematical Engineer, MSc in Applied Mathematics. Co-Organizer TFUG Santiago. Senior Data Scientist at Temis.

Santiago, Chile

Pinned Repositories

Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow
Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron
Language:Jupyter Notebook00
ML-React-App-Template
This is a template for creating a Machine Learning application with its front-end developed using React which interacts with a Flask service as the back-end and makes predictions.
Language:JavaScript00
recommenders
Best Practices on Recommendation Systems
Language:Python00
autoencoders
Language:Jupyter Notebook01

Reac92/recommenders
Best Practices on Recommendation Systems
Reac92/ML-React-App-Template
This is a template for creating a Machine Learning application with its front-end developed using React which interacts with a Flask service as the back-end and makes predictions.
Reac92/Hands-on-Machine-Learning-with-Scikit-Learn-Keras-and-TensorFlow
Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron