The process of gathering relevant cryptocurrency data from various sources for analysis.

Techniques used to clean and prepare raw data for machine learning, improving quality and accuracy.

Creating new input features from raw data to enhance model performance.

A subset of AI where algorithms learn from data to make predictions or decisions.

A method to predict future values based on previously observed values in a time-ordered sequence.

A statistical method for modeling the relationship between a dependent variable and one or more independent variables.

A type of recurrent neural network ideal for sequence prediction problems, including time series.

A technique for assessing how the results of a statistical analysis will generalize to an independent dataset.

The process of optimizing model parameters that are not learned from the data during training.

Quantitative measures used to assess the performance of a machine learning model.

Examining the differences between observed and predicted values to evaluate model accuracy.

The graphical representation of data to identify patterns, trends, and insights.

The condition of a dataset, characterized by accuracy, completeness, reliability, and relevance.

Identifying outliers or unusual data points that differ significantly from the rest of the dataset.

An approach to analyzing datasets to summarize their main characteristics, often using visual methods.

Using statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data.

The process of scaling individual data points to fit within a specific range, improving model performance.

Visual interfaces that display key metrics and trends, allowing users to explore data dynamically.

A popular data visualization tool used for converting raw data into an understandable format.

A Python library used for creating static, animated, and interactive visualizations in Python.

A method for validating time series models by training on past data and testing on subsequent data.

The process of making decisions based on data analysis rather than intuition or observation.

A digital or virtual currency that uses cryptography for security and operates on decentralized networks.

General direction in which the market is moving, influenced by various economic factors.

A measure of how well a machine learning model makes predictions compared to actual outcomes.