Using fastai and CNNs to predict stock prices

WACV2021 - A Weakly Supervised Consistency-based Learning Method for COVID-19 Segmentation in CT Images

Recurrent Graph Evolution Neural Network (ReGENN) using Graph Soft Evolution (GSE)

Draft of the fastai book

Summaries of papers on machine learning, computer vision, autonomous robots etc.

Quick performance check of Pytorch implementation of YoloV4

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.

Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.

A simple baseline for one-shot multi-object tracking

Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.

Practical Deep Learning for Time Series / Sequential Data using fastai/ Pytorch

Source code and data for my talk at Big Things 2019

Practical notebooks for Khipu 2019, held in Universidad de la República in Montevideo.

Practical Deep Learning resources for Time series analysis and forecasting

This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.

Step-by-step tutorial to improve understanding of common operators in Deep Learning frameworks.

Face classification on JavaScript

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…