Stars
An evolving, end-to-end reference for collecting and augmenting data, training, evaluating, and deploying embodied AI systems. Accelerate physical AI with cloud-first pipelines, reproducible workfl…
Inspired by Tony Stark's robotic assistant Dum-E, the mission of this project is to create an intelligent, voice & vision enabled AI agent with robotic arm(s) capable of real-time human interaction…
Serverless patterns. Learn more at the website: https://serverlessland.com/patterns.
Python SDK for transforming any AI agent into a production-ready application. Framework-agnostic primitives for runtime, memory, authentication, and tools with AWS-managed infrastructure.
Example projects using the AWS CDK
A generative AI tool to boost productivity by transcribing and analyzing audio or video recordings containing speech
Tutorial Materials for "The Fundamentals of Modern Deep Learning with PyTorch" workshop at PyCon 2024
WTTE-RNN a framework for churn and time to event prediction
MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automate…
A topic-centric list of HQ open datasets.
Implementation of different ML Algorithms from scratch, written in Python 3.x
An open-source data logging library for machine learning models and data pipelines. 📚 Provides visibility into data quality & model performance over time. 🛡️ Supports privacy-preserving data collec…
Hummingbird compiles trained ML models into tensor computation for faster inference.
This repo contains my coursework, assignments, and Slides for Natural Language Processing Specialization by deeplearning.ai on Coursera
Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".
XAI - An eXplainability toolbox for machine learning
Udacity NLP Nanodegree project
A collection of machine learning examples and tutorials.
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
This repository aims to map the ecosystem of artificial intelligence guidelines, principles, codes of ethics, standards, regulation and beyond.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Algorithms for explaining machine learning models
The fastai book, published as Jupyter Notebooks
TensorFlow code and pre-trained models for BERT
Propensity models make true predictions about a customer’s future behavior. With propensity models you can truly anticipate a customer's future behavior. Here we focus on building a combination of …
Customer churn Modelling
Train machine learning models within a 🐳 Docker container using 🧠 Amazon SageMaker.
Tensorflow, Luminoth Based Table Detection and Extraction
Visualizer for neural network, deep learning and machine learning models