GitHub - mikeaddison93/Neural-Stock-Market-Prediction: Uses back-propagating artificial neural networks (ANNs) and historic stock market prices to predict the future trend of stock exchange. GitHub - mikeaddison93/neural-network-stock-predictor: Semester project for COS 470 (Artifical Intelligence) at the University of Maine. GitHub - mikeaddison93/StockPredictionRNN: High Frequency Trading Price Prediction using LSTM Recursive Neural Networks. Stock-prediction: A long term short term memory recurrent neural network to predict stock data time series. Welcome — Theano 0.8.2 documentation. Theano is a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently.
Theano features: tight integration with NumPy – Use numpy.ndarray in Theano-compiled functions.transparent use of a GPU – Perform data-intensive computations much faster than on a CPU.efficient symbolic differentiation – Theano does your derivatives for functions with one or many inputs.speed and stability optimizations – Get the right answer for log(1+x) even when x is really tiny.dynamic C code generation – Evaluate expressions faster.extensive unit-testing and self-verification – Detect and diagnose many types of errors. Theano has been powering large-scale computationally intensive scientific investigations since 2007.
But it is also approachable enough to be used in the classroom (University of Montreal’s deep learning/machine learning classes).