Data Science

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Across
  1. 1. A type of model that uses past values to forecast future values
  2. 3. A data point that is significantly different from the others
  3. 5. A technique to map large data to a fixed-size index
  4. 9. A measure of the linear relationship between two variables
  5. 10. A resampling technique to estimate statistical variability
  6. 13. A multi-dimensional array used in deep learning
  7. 17. A function used to introduce non-linearity in a neural network
  8. 19. A technique to enable linear algorithms to operate in non-linear spaces
  9. 20. The process of finding the best parameters for a model
  10. 21. A group of similar data points
  11. 23. A mathematical function describing the probability of different values
  12. 26. A statistical model to predict continuous outcomes
  13. 27. A basic computing unit in a neural network
  14. 29. A measure of uncertainty or randomness in a probability distribution
  15. 31. A variable that influences both the dependent variable and independent variable, causing a spurious association.
Down
  1. 2. A representation of categorical data in a dense vector space
  2. 4. A characteristic or attribute of a dataset used in modeling
  3. 6. A phenomenon where a model is too complex and fits the training data too well
  4. 7. A systematic error or distortion in a model or algorithm
  5. 8. The process of selecting a subset of data from a larger population
  6. 11. The process of evaluating a model's performance on unseen data
  7. 12. A measure of the rate of change of a function with respect to its inputs
  8. 14. A technique to scale data to a common range
  9. 15. A mathematical system that undergoes transitions between states according to probabilistic rules
  10. 16. A combination of multiple models to improve performance
  11. 18. A statement or assumption tested using data and statistical methods
  12. 22. The process of selecting and transforming raw data into suitable features for modeling
  13. 24. An ensemble learning method using multiple decision trees
  14. 25. A technique to prevent overfitting by adding a penalty term to the loss function
  15. 28. A function used to transform data into a higher-dimensional space
  16. 30. A dimensionality reduction technique using orthogonal components