tejaslodaya's Stars
facebook/prophet
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
yandexdataschool/nlp_course
YSDA course in Natural Language Processing
coderQuad/New-Grad-Positions
A collection of New Grad full time roles in SWE, Quant, and PM.
awslabs/gluonts
Probabilistic time series modeling in Python
jmcarpenter2/swifter
A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner
arviz-devs/arviz
Exploratory analysis of Bayesian models with Python
pionxzh/chatgpt-exporter
Export and Share your ChatGPT conversation history
palantir/pyspark-style-guide
This is a guide to PySpark code style presenting common situations and the associated best practices based on the most frequent recurring topics across the PySpark repos we've encountered.
roma-glushko/awesome-distributed-system-projects
🚀 List of distributed system projects for inspiration and learning to build distributed services from real world examples
boxuancui/DataExplorer
Automate Data Exploration and Treatment
executablebooks/sphinx-autobuild
Watch a Sphinx directory and rebuild the documentation when a change is detected. Also includes a livereload enabled web server.
tejaslodaya/timeseries-clustering-vae
Variational Recurrent Autoencoder for timeseries clustering in pytorch
jzarnett/ece459
ECE 459: Programming for Performance
ckaestne/seai
CMU Lecture: Machine Learning In Production / AI Engineering / Software Engineering for AI-Enabled Systems (SE4AI)
rstudio/pool
Object Pooling in R
Azure/doAzureParallel
A R package that allows users to submit parallel workloads in Azure
Swiggy/Moo-GBT
Library for Multi-objective optimization in Gradient Boosted Trees
josepm/MP_Pandas
Pandas' group-by/apply with multiprocessing
trnnick/mapa
MAPA package for R