We present a new click model for processing click logs and predicting relevance and appeal for query–document pairs in search results. Our model is a simplified version of the task-centric click model but outperforms it in an experimental comparison.Fishkov Alexander...
Netron - Visualizer for neural network and machine learning models. (Source Code) MIT Python/Nodejs Offen - Fair, lightweight and open web analytics tool. Gain insights while your users have full access to their data. (Demo, Source Code) Apache-2.0 Go/Docker Open Web Analytics - Web analyt...
ClickModels is a small set of Python scripts for the user click models initially developed at Yandex. A Click Model is a probabilistic graphical model used to predict search engine click data from past observations. This project is aimed to deal with cli
Tensors and Dynamic neural networks in Python with strong GPU acceleration 83 storybookjs/storybook TypeScript 85.047k Storybook is the industry standard workshop for building, documenting, and testing UI components in isolation 84 neovim/neovim Vim Script 84.878k Vim-fork focused on extensib...
model is generated on a more powerful computer before being ported over to the microcontroller platform. But that’s all par for the course in AI and machine learning. If you’re looking to take a step up from here,we’d recommend this robot that uses neural networks to learn how to ...
Neural networks are one type of model for machine learning; they have been around for at least 50 years. The fundamental unit of a neural network is a node, which is loosely based on the biological neuron in the mammalian brain. The connections between neurons are also modeled on biological...
We can see that in every column, the best model is always one of our neural embedding models. The final column shows the weighted average score over those cell types, where the weights are the number of such cells in the query set. The best neural embedding model (PT dense 1136 100, ...
In this study, we present a novel deep neural network model, termed RefDNN, for improved prediction of drug resistance and identification of biomarkers related to drug response. RefDNN exploits a collection of drugs, called reference drugs, to learn representations for a high-dimensional gene ...
HackingNeuralNetworks - is a small course on exploiting and defending neural networks. wildcard-certificates - why you probably shouldn't use a wildcard certificate. Don't use VPN services - which is what every third-party "VPN provider" does. awesome-yara - a curated list of awesome YARA ...
ModelThe model is a birectional LSTM neural network with a CRF layer. Sequence of chinese characters are projected into sequence of dense vectors, and concated with extra features as the inputs of recurrent layer, here we employ one hot vectors representing word boundary features for ...