6875 Open source projects that are alternatives of or similar to Neural Tangents

Pythonic Objects

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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).

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Code for reproducing the results from the paper Few Shot Text Classification with a Human in the Loop

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Awesome list of software that I use to do research in medical imaging.

An introduction to implementing a number of scikit-learn classifiers, along with some data exploration

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Joint Vector Spaces

Repository for reading Pascal VOC data in Python, rather than requiring MATLAB to read the XML files.

Jupyter notebooks with exercises for the No bullshit guide to linear algebra.

Distributed deep learning on Hadoop and Spark clusters.

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Keras implementation of GradCAM.

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A documentation browser with support for DevDocs, Dash and Hoogle, written in Haskell and QML

机器学习实战

Time Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms

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A library of probabilistic model based RL algorithms in pytorch

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