Discover the main building blocks of neural networks and understand the three main neural network architectures. Explore the process of solving a regression data problem

Approximate Nearest Neighbor Benchmark

Data Mining Course @ The Open University

Fast and minimal header-only graph-based index for approximate nearest neighbor search (ANNS).

GraphANNS 源链接

The front page to shotit.github.io

perceptron, backprop, RBF, SOM, hopfield nets, autoencoders (no external ML libs)

ISCC Nearest Neighbor Index

The README profile of Shotit.

In this Repository, we intend to implement the DQN and also the DDQN algorithm in case of training an agent to solve the Lunar-Lander problem. there are lots of exciting results after training which have been attached.

Media broker for serving video preview for shotit

Sort the search results of Shotit to increase the correctness of Top1 result by using Keras and Faiss.

This repository contains materials and course projects during attending the Intelligent Systems Course, for more detailed information please have a look at my Final_Report files which have been separately uploaded for each of the projects and consist of all required information about the implementations, analyses, and anything else you may conce…

The frontend of shotit, with full documentation.

The goal is to make an Artificial Neural Network that can predict, based on geo-demographical and transactional information given above, if any individual customer will leave the bank or stay (customer churn). Also, rank all the customers of the bank, based on their probability of leaving.

Provide meta information and utility for shotit, for example, image proxy, cast and poster etc.

Four core workers of shotit: watcher, hasher, loader and searcher.

Naive implementations of some ANNS (Approximate Nearest Neighbor Search) algorithms without any optimization and generalization.

Simple gRPC server for vector searching implemented by Python and Faiss

The ultimate brain of Shotit, in charge of task coordination.