Discord

HASH logoGlossary

Data Science

Autocorrelation

Autocorrelation is a measure of the degree of similarity between any time series and a lagged or offset version of itself over successive time intervals.

Directed Acyclic Graphs

If you don’t know your DAGs from your dogs, you can finally get some clarity and sleep easily tonight. Learn what makes a Directed Acyclic Graph a DAG.

Data Drift

Data Drift is the phenomenon where changes to data degrade model performance.

Data Mesh

Data meshes are decentralized database solutions.

Data Mining

Data Mining is a process applied to find unknown patterns, correlations, and anomalies in data. Through mining, meaningful insights can be extracted from data.

Data Pipelines

Data pipelines are processes that result in the production of data products, including datasets and models.

Ego Networks

Ego networks are a framework for local analysis of larger graphs.

Knowledge Graphs

Knowledge Graphs contextualize data and power insight generation.

Metadata

Metadata is data about data. It’s quite simple, really. Learn more about how it’s used within.

Model Drift

Models tend to become less accurate over time.

Optimization Methods

The key to finding the best solution to any problem.

Parameters

Parameters control specific parts of a system's behavior.

Process Mining

Process mining is an application of data mining with the purpose of mapping an organization’s processes. It is used to optimize operations, and identify weaknesses.

Robustness

Robustness is a measure of a model's accuracy when presented with novel data.

Schemas

Schemas are descriptions of things: agents in simulations, and the actions they take. They help make simulations interoperable, and data more easily understood.

Stochasticity

Stochasticity is a measure of randomness. The state of a stochastic system can be modeled but not precisely predicted.

Synthetic Data Generation

Generating data that mimics real data for use in machine learning.

Time Series Data

Time series data is data that has been indexed, listed, or graphed in time order. For example, the daily closing value of the NASDAQ, the price of a cryptocurrency per second, or a single step in a simulation run.

Discrete vs Continuous Time

In continuous time, variables may have specific values for only infinitesimally short amounts of time. In discrete time, values are measured once per time interval.