rayanaay-ops Goto Github PK

ansible-labs

Bunch of labs for Ansible developers to increase their skills and become better developers

apache_virtualhost_automation

This script allows you to create an entire ,fully configured VirtualHost to serve content for multiple domains. Those hosts are typically used when it is not cost-effective to spin up multiple (virtual) machines to serve out many low-traffic sites.

asymmetric_encryption

RSA Asymmetric Encryption

blockchain-real-time-analysis-iota

This is a Blockchain Application based on IOTA Masked Authenticated Messaging API , to monitor sensor data delivered by embedded system under NodeJS

databricks-certifications

deepchecks

Deepchecks - Tests for Continuous Validation of ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort.

git-practice

Bunch of practice for git, for every developers :)

gmm-anomaly-detection

a Gaussian Mixture Model (GMM) based anomaly detector, inheriting from the GaussianMixture class in scikit-learn. The gmmAnomalyDetector class provides methods for anomaly detection using GMM.

i2c_lcp1768_read-from-sensor

This is a low implementation of internal register addressing of LM75BD sensor using Mbed LCP1768 interfacing with I2C communication protocol.

janathahack-customer_segmentation

Max voting of 4 Optimized Classifiers based on decision tree algorithms

jodie

Replication jodie model

melanoma_detection

minibatchkmeans-vs-kmeans

In this notebook, I compared two famous clustering algorithm, the minibatchkmeans and the regular kmeans on cellular image dataset.

minimal-flask-cicd

This repo serves as a minimalistic template for setting up a Flask web application with Continuous Integration/Continuous Deployment (CI/CD) capabilities.

osic-pulmonary-fibrosis-regression

This is my implementation of the OSIC competition hosted on Kaggle ,where it was about dealing with tabular and images data

otto-recommendation

pytorch-helper

This is a bunch of my pytorch notebooks,where you will find the basis of Pytorch and its implementation of neural networks ,transfer learning etc..;

re-deep-recurrent-nmf-for-speech-separation-by-unfolding-iterative-thresholding

In this code, we propose a different implementation fo the original paper https://arxiv.org/abs/1709.07124 under PyTorch. This architecture is constructed by unfolding the iterations of a sequential iterative soft-thresholding algorithm (ISTA) that solves the optimization problem for sparse nonnegative matrix factorization (NMF) of spectrograms. We name this network architecture deep recurrent NMF (DR-NMF)

re-jodie-recommander-system

Code for our Reproducibility Challenge Paper "Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks".

regression-stacked-svm_randomforest

This is my implementation of a stacked regressor using optimized SVM and random Forest using Optuna.The actual inputs of the combined regressor is a latent representation of 220 inputs compressed into 5 ,extracted using an auto-encoder implemented under Keras

robust-distributed-vgg

This is a simulated environment that conceptualize a network of IOT devices, where every devices contains one part of the pre-trained model represented by a class. I also made the network resilient to electrical disruption and robust to intermediate node fail, by adding an extension layer in the final node that will re-connect the initial node with the final layer

rust-codeforces

Competitive programming using Rust

rust-helper

These are helpers for data structures and examples of key concepts on Rust in ready to use ,inspired from the rust cook book

rustacean-grep

This is a Rust implementation of the famous Grep command in Linux used to search for a String in a file

sturdy-octo-barnacle

RestAPI + Airflow + s3 uploading

vanilla_autoencoder

This is a straight forward implementation of vanilla-autoencoder applied on image compression using Pytorch

variational-autoencoder-for-satellite-imagery

This is my implementation of a special Variational Autoencoder under TF 2.0, which make it possible to squeeze N images to generate one single representation of all the dataset with colors segmentation of the difference objects