A showcase based on the tutorial presented at ML@Enterprise Forum 2018 in Warsaw.

Contains examples for reinforcement learning and deep reinforcement learning using R, Keras (TF) and OpenAI-gym

Active Learning with approximations of Bayesian Convolutional Neural Networks.

This repository contains the necessary scripts to derive off-target models through (1) A neural network framework based on Keras and Tensorflow (2)An autmomated machine learning framework based on AutoGluon

App to carry out simple experiments of the use of LSTM networks in time series forecasting. It allows users to solves univariate and multivariate regression problems by testing different set of features, and comparing the effectiveness of the obtained results.

Machine learning,Deep Learning Data science

R Script for AI Image and Location Recognition that can also generate an automated prompt for AI text-generation of a social media post.

Blood Cell Images Dataset

Research Project in the area of ​​Deep Learning applied to credit risk. This model achieved better results compared to other published papers. This project is focused on the Fintech industry.

Different approaches to solve MNIST problem with convolutional neural networks

Using Keras to build a deep neural network for bladder cancer progression

Srovnání twitterové timeliny pravého a falešného Tomio Okamury jako příklad klasifikace textu