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darts

A python library for easy manipulation and forecasting of time series.

deepfakes

This is the code for "DeepFakes" by Siraj Raval on Youtube

deeplearning-tensorflow-keras

faceswap

Non official project based on original /r/Deepfakes thread. Many thanks to him!

fxforecast

keras-vis

Neural network visualization toolkit for keras

mobilitydata

openpose

OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation

retina-unet

Retina blood vessel segmentation with a convolutional neural network

source-separation-wavenet

A neural network for end-to-end music source separation

spleeter

Deezer source separation library including pretrained models.

stanford-project-predicting-stock-prices-using-a-lstm-network

Stanford Project: Artificial Intelligence is changing virtually every aspect of our lives. Today’s algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is an exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Models that explain the returns of individual stocks generally use company and stock characteristics, e.g., the market prices of financial instruments and companies’ accounting data. These characteristics can also be used to predict expected stock returns out-of-sample. Most studies use simple linear models to form these predictions [1] or [2]. An increasing body of academic literature documents that more sophisticated tools from the Machine Learning (ML) and Deep Learning (DL) repertoire, which allow for nonlinear predictor interactions, can improve the stock return forecasts [3], [4] or [5]. The main goal of this project is to investigate whether modern DL techniques can be utilized to more efficiently predict the movements of the stock market. Specifically, we train a LSTM neural network with time series price-volume data and compare its out-of-sample return predictability with the performance of a simple logistic regression (our baseline model).

tools