Hi, my name's Andrew Chang and I like to build things.
My experience in engineering involves AI/ML, deep learning, natural language processing, and MLOps. I enjoy building out full stack applications on distributed systems with tools like Python, Docker, and Kubernetes.
I am the creator and maintainer of AdaptNLP, Godel, GoldNLP, ML Docker images, and other tools/services.
Simple Jupyter Lab and Hub management platform with pre-configured environment runtimes supporting a variety of tools, libraries, and GPUs.
A framework for deploying serializable and optimizable neural net models at scale in production via the NVIDIA Triton Inference Server.
A high level framework and library for running, training, and deploying state-of-the-art NLP models. Built atop Flair and Hugging Face Transformers, it provides a modular and adaptive approach to a variety of NLP tasks.
A learning rate finder for the 1cycle learning policy. Automates the selection of a recommended learning rate in FastAI with an interval slide rule technique.
Docker images for ML/AI applications with containers ranging from CUDA-compatible jupyter servers and environments to Kops/k8s plugins for CI/CD workflows.
State-of-the-art Text Classification Made Easy with AdaptNLP
Andrew Chang, Brian Sacash
State-of-the-art NLP Made Easy with AdaptNLP
Andrew Chang, Brian Sacash