Search Results for "hyper-quant"

hyper is a fast HTTP implementation written in and for Rust. A Client for talking to web services. A Server for building those web services. Blazing fast thanks to Rust. High concurrency with non-blocking sockets. HTTP/1 and HTTP/2 support. hyper is a relatively low-level library, meant to be a building block for libraries and applications.

...Juniper does not include a web server - instead it provides building blocks to make integration with existing servers straightforward. It optionally provides a pre-built integration for the Actix, Hyper, Iron, Rocket, and Warp frameworks, including embedded Graphiql and GraphQL Playground for easy debugging. The best place to get started is the Juniper Book, which contains guides with plenty of examples, covering all features of Juniper. Juniper supports the full GraphQL query language according to the specification (October 2021), including interfaces, unions, schema introspection, and validations. ...

Neural Network Intelligence is an open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate feature engineering, neural architecture search, hyperparameter tuning and model compression. The tool manages automated machine learning (AutoML) experiments, dispatches and runs experiments' trial jobs generated by tuning algorithms to search the best neural architecture and/or hyper-parameters in different training environments like Local Machine, Remote Servers, OpenPAI, Kubeflow, FrameworkController on K8S (AKS etc.) ...

TF Quant Finance is a high-performance library of quantitative finance components built on TensorFlow, aimed at research and production workloads. It implements pricing engines, risk measures, stochastic models, optimizers, and random number generators that are differentiable and vectorized for accelerators. Users can value options and fixed-income instruments, simulate paths, fit curves, and calibrate models while leveraging TensorFlow’s jit compilation and automatic differentiation. ...

MLBox is a powerful Automated Machine Learning python library. Fast reading and distributed data preprocessing/cleaning/formatting. Highly robust feature selection and leak detection. Accurate hyper-parameter optimization in high-dimensional space. State-of-the-art predictive models for classification and regression (Deep Learning, Stacking, LightGBM,...) Prediction with model interpretation. MLBox has been developed and used by many active community members. Your help is very valuable to make it better for everyone.

If you have ever tried to locate files, classes, and resources buried amongst an ever shifting locus of ZIP and / or JAR files, we feel your pain! After spending far too much time searching hundreds of archives for moving targets, I decided to write JarOMine. Originally designed for locating Java classes, JarOMine works equally well with ZIP archives, too.

The project contains classes for implementation of binomial option pricing model and Newton method for finding roots of a function in Java. You can browse the source code and download the full distribution package.

Fast Matrix for Java (fm4j) is a general-purpose matrix utility library for computing with dense matrices. fm4j encapsulated different underlying implementations and select the optimal one in run-time depending on the size of the input matrix. Moreover, fm4j employs Java (Tm) Concurrency to take advantage of the computation power of multi-cor processors.

Surinam adds hyper-dynamic behavior to software by deploying and managing user-developed services that can come and go over time. This allows applications to be developed as loosely-coupled aggregations of services that can be modified in real time.