josiahdavis

amazon-sagemaker-tsp-deep-rl

train, deploy, and make inferences using deep reinforcement learning to solve the Travelling Salesperson Problem

ec2-data-science-vim-tmux-zsh

A simple template to set up basic Vim, Tmux, Zsh for the Deep Learning AMI Amazon Linux 2 for data scientists.

torchserve-eks

How to deploy TorchServe on an Amazon EKS cluster for inference.

mlmax

Example templates for the delivery of custom ML solutions to production so you can get started quickly without having to make too many design choices.

plit

A Matplotlib wrapper that automates the undifferentiated heavy-lifting of writing boilerplate code while maintaining the power and feel of Matplotlib.

aws-reference

Reference files useful for compute on AWS

CCI

Workshop for Deloitte's Center for Customer Insights

DecisionTrees

Tutorial for Decision Trees in Python

document-understanding-solution

Example of integrating & using Amazon Textract, Amazon Comprehend, Amazon Comprehend Medical, Amazon Kendra to automate the processing of documents for use cases such as enterprise search and discovery, control and compliance, and general business process workflow.

repgpt

Reproducing GPT2

josiahdavis/repgpt

Reproducing GPT2

josiahdavis/aws-reference

Reference files useful for compute on AWS

josiahdavis/document-understanding-solution

Example of integrating & using Amazon Textract, Amazon Comprehend, Amazon Comprehend Medical, Amazon Kendra to automate the processing of documents for use cases such as enterprise search and discovery, control and compliance, and general business process workflow.

josiahdavis/dotfiles

dot files mean to be cloned and linked during the launch of a new EC2

josiahdavis/getting-started-batch

How to use AWS Batch Array Jobs with Python and S3 for input/output.

josiahdavis/profiling-lm

Reference files for programming with PyTorch

josiahdavis/project-skeleton

Simple project structure

josiahdavis/amazon-sagemaker-examples

Example notebooks that show how to apply machine learning, deep learning and reinforcement learning in Amazon SageMaker

josiahdavis/amazon-sagemaker-feature-store-streaming-aggregation

This repo provides an end-to-end example of using streaming feature aggregation with the Amazon SageMaker Feature Store.

josiahdavis/cref

Reference Guide for Learning C

josiahdavis/docker-aws-cdk

🐳 Containerized AWS CDK on alpine to avoid having to install CLI on Dev or CI/CD machines.

josiahdavis/josiahdavis

josiahdavis/josiahdavis.github.io

Personal site built with jekyll

josiahdavis/lambdamap

josiahdavis/ml-notebooks

Machine Learning Notebooks

josiahdavis/or-rl-benchmarks

The source code for the paper: 'ORL: Reinforcement Learning Benchmarks for Online Stochastic Optimization Problems'

josiahdavis/PH252D

Repo for PH252D group project

josiahdavis/py-ds-template

Cookiecutter template for a Python data science project

josiahdavis/python-deequ

Python API for Deequ

josiahdavis/python-project-skeleton

A simple project structure for Python

josiahdavis/pyutil

Odds and ends

josiahdavis/pyutil-1

Collections of code fragments

josiahdavis/sagemaker-containers

WARNING: This package has been deprecated. Please use the SageMaker Training Toolkit for model training and the SageMaker Inference Toolkit for model serving.

josiahdavis/sagemaker-tensorflow-serving-container

A TensorFlow Serving solution for use in SageMaker.

josiahdavis/scikit-learn

scikit-learn: machine learning in Python

josiahdavis/tabular

Example of how to get started modelling tabular data in pytorch

josiahdavis/testing

template testing

josiahdavis/torchserve-eks

How to deploy TorchServe on an Amazon EKS cluster for inference.

josiahdavis/transformers

🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.

josiahdavis/TSP_Transformer

Code for TSP Transformer