Pinned Repositories
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's Repositories
josiahdavis/CCI
Workshop for Deloitte's Center for Customer Insights
josiahdavis/DecisionTrees
Tutorial for Decision Trees in Python
josiahdavis/python_data_analysis
Workshop: Python for Data Analysis
josiahdavis/stocks222
josiahdavis/assume-role
Change roles from the CLI with the same AWS account.
josiahdavis/awesome-R
A curated list of awesome R frameworks, packages and software.
josiahdavis/base_python
Workshop: Python
josiahdavis/bootstrapping
josiahdavis/DAT4
General Assembly's Data Science course in Washington, DC
josiahdavis/Dat6-students
josiahdavis/deploy-ml-sagemaker
Simple example of deploying Machine Learning model with with SageMaker and making inference.
josiahdavis/earl
josiahdavis/energy
Modeling Electricity Usage Trends
josiahdavis/extractive-sentence-summarization
josiahdavis/generations
Analyze cross section of data from 1989 (Baby Boomers), 1998 (Generation X) and 2006 (Millennials) to assess differences in work values.
josiahdavis/intro_to_cart
Slides: CART algorithm
josiahdavis/learningdatascience
landing page for learning data science site
josiahdavis/marty_rep
this test
josiahdavis/nlp-in-R
Script and data for performing Natural Language Processing tasks in R
josiahdavis/stat243
assignments for stat243
josiahdavis/stat243FinalProject
Stat 243 Final Project
josiahdavis/titanic_kaggle_comp
Competition: Survival on the Titanic
josiahdavis/using_python_data_science