mehravehs Goto Github PK

amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

camera2otsublinking

This set of codes are built on top of Camera2 API, and allow for capturing and saving raw images while blinking the flashlight. This was part of the project on Visible Light Communication (VLC).

cmp

Connectome Mapper

ctci

Cracking the Coding Interview, 5th Edition

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

faiss

A library for efficient similarity search and clustering of dense vectors.

flask-ml-azure-serverless

Deploy Flask Machine Learning Application on Azure App Services

gitignore

A collection of useful .gitignore templates

imagenet-simple-labels

Simpler human-readable labels for ImageNet 🏷

json

JSON for Modern C++

mcertikos---os-project

Project of the course Operating System

mehravehs.github.io

Please visit: www.mehravehsalehi.com

networkvisualization

This code provides a framework for the network visualization of functional connectivity matrices.

pytorch-sample-codes

rest

salmonella

This set of codes aims at classifying different species using their ATP features. The classification is employed using a fully cross-validated data-driven approach.

spark-nlp

State of the Art Natural Language Processing

twelvemonkeys

TwelveMonkeys ImageIO: Additional plug-ins and extensions for Java's ImageIO

under_construction

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

webcam-capture

Project goal is to give users possibility to access build-in or connected via USB webcams or remote IP / network cameras directly from Java code. Using provided libraries user is able to read camera images and detect motion. Main project consist of several sub projects - the root one, which contains required classes, build-in webcam driver compatible with Windows, Linux and Mac OS, which can stream images as fast as your camera can serve them (up to 50 FPS). Main project can be used standalone, but user is able to replace build-in driver with different one - such as OpenIMAJ, GStreamer, V4L4j, JMF, LTI-CIVIL, FMJ, etc.