Leo Lorenzo Luis's repositories
BMW-YOLOv3-Training-Automation
This repository allows you to get started with training a state-of-the-art Deep Learning model with little to no configuration needed! You provide your labeled dataset and you can start the training right away and monitor it in many different ways like TensorBoard or a custom REST API and GUI. Training with YOLOv3 has never been so easy.
ignite-learning-paths-training-aiml
Microsoft Ignite Learning Path, Train the Trainer materials: Developers Guide to AI
OpenDiablo2
An open source re-implementation of Diablo 2
TensorflowTypeProvider
This Type Provider aims to eliminate the need for ‘magic strings’ associated with accessing pre-trained Tensorflow Graphs. Typed access to NPY/NPZ is also included.
danger
🚫 Stop saying "you forgot to …" in code review (in Ruby)
dapr
Dapr is a portable, event-driven, runtime for building distributed applications across cloud and edge.
imagededup
😎 Finding duplicate images made easy!
polynote
A better notebook for Scala (and more)
strapi
🚀 Open source Node.js Headless CMS to easily build customisable APIs
Reactors
Content for Microsoft Reactor Workshops
kubeflow
Machine Learning Toolkit for Kubernetes
truffleHog
Searches through git repositories for high entropy strings and secrets, digging deep into commit history
fast-dna
An unopinionated system of components, development tools, and utilities used à la carte or as a suite to build enterprise-grade websites and applications.
ModSecurity
ModSecurity is an open source, cross platform web application firewall (WAF) engine for Apache, IIS and Nginx that is developed by Trustwave's SpiderLabs. It has a robust event-based programming language which provides protection from a range of attacks against web applications and allows for HTTP traffic monitoring, logging and real-time analysis. With over 10,000 deployments world-wide, ModSecurity is the most widely deployed WAF in existence.
nlp
Natural Language Processing Best Practices & Examples
cobalt
Infrastructure turn-key solution for app service workloads
EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
ComputerVision
Best Practices, code samples, and documentation for Computer Vision.
sagemaker-pytorch-container
Docker container for running PyTorch scripts to train and host PyTorch models on SageMaker
bedrock
Automation for Production Kubernetes Clusters with a GitOps Workflow
FSharpPlus
Extensions for F#
non-profit-blockchain
Builds a blockchain network and application to track donations to non-profit organizations, using Amazon Managed Blockchain
talk-kafka-zipkin
Demo material from talk about tracing Kafka-based applications with Zipkin
gnes
GNES is Generic Neural Elastic Search, a cloud-native semantic search system based on deep neural network.
Trill
Trill is a single-node query processor for temporal or streaming data.
qsharp-compiler
Q# compiler, command line tool, and Q# language server