Pinned Repositories
AMIGOS
Having various signals describing the modalities the aim of the project is to develop Deep Learning Model accepting the signals as an input and providing recognized emotion as an output. Emotion recognition method is build using AMIGOS database.
arima-vs-lstm-on-nasdaq-stock-exchange-data
This study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange.
DariuszKobiela
Config files for my GitHub profile.
deep-neural-networks-for-sentiment-analysis-in-stock-exchange-data
This work is the extension of the repository arima-vs-lstm-on-nasdaq-stock-exchange-data made in order to continue research on other statistical and deep learning models with the usage of sentiment analysis.
DigitPredictorAI
MNIST Project
identification-and-classification-of-sea-going-vessels-using-satellite-images
ngcf-neural-graph-collaborative-filtering
transactional-data-analysis
Having transactional data about various companies, we would like to analise them and predict the companies prices.
vehicle-type-classification-based-on-image-data
The aim of the project is to create a neural network model, which basing on the input data in the form of an image files will be able to classify the type of the vehicle.
vehicle-type-recognition-based-on-audio-data
The aim of the project is to create a neural network model, which basing on the input data in the form of an audio files will be able to recognize the type of the vehicle passing.
DariuszKobiela's Repositories
DariuszKobiela/AMIGOS
Having various signals describing the modalities the aim of the project is to develop Deep Learning Model accepting the signals as an input and providing recognized emotion as an output. Emotion recognition method is build using AMIGOS database.
DariuszKobiela/identification-and-classification-of-sea-going-vessels-using-satellite-images
DariuszKobiela/arima-vs-lstm-on-nasdaq-stock-exchange-data
This study compares the results of two completely different models: statistical one (ARIMA) and deep learning one (LSTM) based on a chosen set of NASDAQ data. Both models are used to predict daily or monthly average prices of chosen companies listed on the NASDAQ stock exchange.
DariuszKobiela/DariuszKobiela
Config files for my GitHub profile.
DariuszKobiela/deep-neural-networks-for-sentiment-analysis-in-stock-exchange-data
This work is the extension of the repository arima-vs-lstm-on-nasdaq-stock-exchange-data made in order to continue research on other statistical and deep learning models with the usage of sentiment analysis.
DariuszKobiela/ngcf-neural-graph-collaborative-filtering
DariuszKobiela/transactional-data-analysis
Having transactional data about various companies, we would like to analise them and predict the companies prices.
DariuszKobiela/vehicle-type-classification-based-on-image-data
The aim of the project is to create a neural network model, which basing on the input data in the form of an image files will be able to classify the type of the vehicle.
DariuszKobiela/vehicle-type-recognition-based-on-audio-data
The aim of the project is to create a neural network model, which basing on the input data in the form of an audio files will be able to recognize the type of the vehicle passing.
DariuszKobiela/DigitPredictorAI
MNIST Project
DariuszKobiela/DP_Pipes
Distributed Processing - pipes examples
DariuszKobiela/identification-and-classification-of-sea-going-vessels-using-satellite-images-2
identification-and-classification-of-sea-going-vessels-using-satellite-images-2