Nino's repositories
adstex
Automated generation of NASA ADS bibtex entries directly from citation keys in your TeX source files
AST337-Fall2018
Lab Materials for the ASTR 337 ("Observational Techniques I") Course at Amherst College - Fall 2018
astrometry.net
Astrometry.net -- automatic recognition of astronomical images
astroNN
Deep Learning for Astronomers with Tensorflow
Institution-Classification
NASA Interns code on classifying institutions
ReviewerExtractor
It contains all the work done by NASA HQ interns about it
datalab-client
Data Lab Client Commands and Interfaces
EveningOfPythonCoding
This page contains information on the Evening of Python coding held in Austin
InteractivePoster
Package with template interactive poster in Dash
JWSTUserTraining2016
User Training in JWST Data Analysis II
languagecheck
Improve the language of your paper before submission
MalloryNASA_Internship
Code from my NASA internship summer 2023
mirapy
MiraPy: A Python package for Deep Learning in Astronomy
MulensModel
Microlensing Modelling package
NASA-Internship
This repository contains the final deliverables of the three seasons of my NASA Internship, from Summer 2022 to Spring 2023.
NASAInternship
This repository is to test out the user compatibility of my code !
NNfSiX
Neural Networks from Scratch in various programming languages
ObservingStrategy
A community white paper about LSST observing strategy, with quantifications via the the Metric Analysis Framework.
pandeia-imaging1
A simple wrapper around the Pandeia engine to facilitate coronagraphy calculations for JWST
PypeIt
The Python Spectroscopic Data Reduction Pipeline
Reviewer-Extractor
Kaniyah's code
SIK-Guide-Code
Example code from the SparkFun Inventor's Kit Guide.
sims_maf_contrib
Contributed code for MAF (sims_maf)
StarbucksStoreScraping
code for scraping starbucks store data from Store Locator API
StatisticalMethods
Course notes and resources for Stanford University graduate lecture course PHYS366: Special Topics in Astrophysics: Statistical Methods
tutorials
Notebook Tutorials for Deep Learning using MiraPy