Pinned Repositories
body-pix
Body segementation React app using body pix model from tfjs
datacamp_tutorials
DL-Lab
Deep Learning Lab files updated weekly
hello-world
LSTM_GRU_CIPLA
prudhvi-somisetty
prudhvi-somisetty.github.io
Stock-price-prediction-using-GAN
In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
prudhvi-somisetty's Repositories
prudhvi-somisetty/DL-Lab
Deep Learning Lab files updated weekly
prudhvi-somisetty/body-pix
Body segementation React app using body pix model from tfjs
prudhvi-somisetty/datacamp_tutorials
prudhvi-somisetty/hello-world
prudhvi-somisetty/LSTM_GRU_CIPLA
prudhvi-somisetty/prudhvi-somisetty
prudhvi-somisetty/prudhvi-somisetty.github.io
prudhvi-somisetty/Stock-price-prediction-using-GAN
In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.
prudhvi-somisetty/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.