Displaying 1 to 6 from 6 results

deepvariant - DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data

  •    Python

DeepVariant is an analysis pipeline that uses a deep neural network to call genetic variants from next-generation DNA sequencing data.DeepVariant is a suite of Python/C++ programs that run on any Unix-like operating system. For convenience the documentation refers to building and running DeepVariant on Google Cloud Platform, but the tools themselves can be built and run on any standard Linux computer, including on-premise machines. Note that DeepVariant currently requires Python 2.7 and does not yet work with Python 3.

tfjs - A WebGL accelerated, browser based JavaScript library for training and deploying ML models.

  •    Javascript

TensorFlow.js is an open-source hardware-accelerated JavaScript library for training and deploying machine learning models. Develop ML in the Browser Use flexible and intuitive APIs to build models from scratch using the low-level JavaScript linear algebra library or the high-level layers API.

pwnagotchi - (⌐■_■) - Deep Reinforcement Learning instrumenting bettercap for WiFi pwning.

  •    Javascript

Pwnagotchi is an A2C-based "AI" leveraging bettercap that learns from its surrounding WiFi environment to maximize the crackable WPA key material it captures (either passively, or by performing authentication and association attacks). This material is collected as PCAP files containing any form of handshake supported by hashcat, including PMKIDs, full and half WPA handshakes. Instead of merely playing Super Mario or Atari games like most reinforcement learning-based "AI" (yawn), Pwnagotchi tunes its parameters over time to get better at pwning WiFi things to in the environments you expose it to.




SiaNet - An easy to use C# deep learning library with CUDA/OpenCL support

  •    CSharp

Developing a C# wrapper to help developer easily create and train deep neural network models. The below is a classification example with Titanic dataset. Able to reach 75% accuracy within 10 epoch.

deepbedmap - Going beyond BEDMAP2 using a super resolution deep neural network

  •    Jupyter

Going beyond BEDMAP2 using a super resolution deep neural network. Also a convenient flat file data repository for high resolution bed elevation datasets around Antarctica. Launch in Pangeo Binder (Interactive jupyter notebook/lab environment in the cloud).






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