Fabio M. Graetz, Ph.D.

Tensorflow implementation of Deepminds dqn with double dueling networks

Visualizing CNN filters using PyTorch

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DeViSE model (zero-shot learning) trained on ImageNet and deployed on AWS using Docker

Creates bifurcation diagrams of real discrete one dimensional chaotic maps

Notes and homework assignments to the course "Intro to Parallel Programming" by Nvidia on Udacity

My emacs setup

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Kubernetes operator for managing the lifecycle of Apache Spark applications on Kubernetes.

Specification of the IR for Flyte workflows and tasks. Also Interfaces for all backend services. https://docs.flyte.org/projects/flyteidl/en/stable/

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Training algorithm design and data structures

Fastai: Deep Learning from the foundations

The 3rd edition of course.fast.ai

An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models

Connect, secure, control, and observe services.

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Hydra is a framework for elegantly configuring complex applications

Kubernetes-native workflow automation platform for complex, mission-critical data and ML processes at scale. It has been battle-tested at Lyft, Spotify, Freenome, and others and is truly open-source.

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

Open source platform for the machine learning lifecycle

Cracking the Coding Interview 6th Ed. C++ Solutions

Flyte Backend Plugins contributed by the Flyte community.

Extensible Python SDK for developing Flyte tasks and workflows. Simple to get started and learn and highly extensible.

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Flyte User-Guides and Tutorials - https://flytecookbook.readthedocs.io

Generic templated configuration management for Kubernetes, Terraform and other things

The user interface for Flyte

Kubernetes-native Job Queueing

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

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Control Plane for Flyte. Flyteadmin is a gRPC + REST Service written in golang and uses a RDBMs to store meta information and management information for Flyte Tasks and Workflows.

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

Source files for the website

Code of the official webpage of onnx

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

FlytePropeller is a Kubernetes native operator, that executes Flyte Workflows and Tasks. It has its own kubectl-flyte CLI to interact and is extensible using the flyteplugins/pluginmachinery interface