berkidem
Data Scientist at Burning Glass Institute. PhD in Economics from Penn State.
@Burning-Glass-Institute Miami, FL
berkidem's Stars
cid-harvard/py-ecomplexity
Python package to compute economic complexity and associated variables
karpathy/LLM101n
LLM101n: Let's build a Storyteller
drivendataorg/cookiecutter-data-science
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
keyonvafa/sequential-rationales
Rationales for Sequential Predictions
keyonvafa/career-code
Code for the paper "CAREER: Transfer Learning for Economic Prediction of Labor Sequence Data"
oedokumaci/templatex
Template repository for Latex projects.
karpathy/llm.c
LLM training in simple, raw C/CUDA
tinygrad/tinygrad
You like pytorch? You like micrograd? You love tinygrad! ❤️
igrigorik/ga-beacon
Google Analytics collector-as-a-service (using GA measurement protocol).
AnswerDotAI/fsdp_qlora
Training LLMs with QLoRA + FSDP
crewAIInc/crewAI
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.
microsoft/autogen
A programming framework for agentic AI 🤖
hundredblocks/transcription_demo
duyguozc/topic_modeling_tweets
Topic Modeling of Twitter Comments
QuantEcon/MatchingMarkets.py
Python toolbox for simulation of matching markets in economics
oedokumaci/gale-shapley
Python implementation of the Gale-Shapley Algorithm.
py-why/EconML
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
uber/causalml
Uplift modeling and causal inference with machine learning algorithms
karpathy/minbpe
Minimal, clean code for the Byte Pair Encoding (BPE) algorithm commonly used in LLM tokenization.
rspeer/wordfreq
Access a database of word frequencies, in various natural languages.
thomasf/solarized-css
eaclark07/sms
mangiucugna/json_repair
A python module to repair invalid JSON, commonly used to parse the output of LLMs
ranaroussi/yfinance
Download market data from Yahoo! Finance's API
johnmarktaylor91/torchlens
Package for extracting and mapping the results of every single tensor operation in a PyTorch model in one line of code.
usememos/memos
An open-source, lightweight note-taking solution. The pain-less way to create your meaningful notes.
revant-io/cdk-cost-limit
A Collection of CDK Constructs to Deploy Cost-Aware Self-Limiting Resources
haimgel/display-switch
Turn a $30 USB switch into a full-featured multi-monitor KVM switch
the-turing-way/the-turing-way
Host repository for The Turing Way: a how to guide for reproducible data science
karpathy/svmjs
Support Vector Machine in Javascript (SMO algorithm, supports arbitrary kernels) + GUI demo