five essential python concepts for data pros
a concise guide to list comprehensions, decorators, context managers, argument packing, and dunder methods for writing efficient, maintainable python code.
topic
data science
daily brief: 2026-05-16
ai reshapes personal finance, data science, and space exploration while talent shifts and energy strains emerge.
daily brief: 2026-05-15
ai reshapes energy, finance, and research while talent shifts and new tools emerge.
time-series feature engineering with python itertools
build efficient time series features like lags, rolling windows, and seasonal interactions using python's itertools module.
ai agents reshape data science in 2026
ai agents will automate data cleaning, feature engineering, and model tuning, letting data scientists focus on strategy and problem-solving.
turboquant compresses llm caches to 3 bits
google's turboquant uses polarquant and qjl to cut kv cache memory by over 5x without retraining or accuracy loss.
regret metric exposes cost of strict false discovery control
a new weighted regret metric reveals deterministic online multiple testing procedures suffer linear regret from false negatives, and a decoupled wrapper fixes it.
adaptive importance sampling fixes quantized rl training
a new method corrects policy gradient bias from low-precision rollouts in llm reinforcement learning, preventing training collapse.
daily brief: 2026-05-14
openai eyes legal action against apple, recursive superintelligence lands $650m, and cerebras goes public in a busy ai news day.
5 small language models for agentic tool calling
five compact open-weight language models that support structured tool calling for agentic ai workflows.
how weak-to-strong generalization works in neural networks
a new theory shows that fine-tuning a strong model on a weak model's outputs can elicit pre-trained knowledge without losing general skills.
online conformal prediction with nested sets
new methods produce nested prediction sets across multiple coverage levels for simultaneous uncertainty quantification in online settings.
10 github repos to learn self-hosting
a curated list of github repositories that teach self-hosting skills from discovery to deployment, monitoring, and secure access.
spatial adapter adds structured residuals to frozen models
a new post-hoc layer gives frozen predictors a spatial view of errors and a closed-form covariance without retraining.
valid inference after active data collection
a new framework enables valid statistical inference when reusing data from adaptive sampling methods like bayesian optimization.
adamw-trained transformers converge to ode system
large-depth transformers trained with adamw converge uniformly to a forward-backward ode system, with explicit convergence rates.
decentralized novelty detection with quantized model exchange
a method for decentralized novelty detection that controls false discovery rate without sharing raw data, using low-precision model exchange.
python scripts for time series analysis
five reusable python scripts handle common time series tasks like resampling, anomaly detection, decomposition, forecasting, and multi-series comparison.