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Crossword Puzzle
Crossword Puzzle

THE ML Mind Maze

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THE ML Mind Maze

Crossword Puzzle

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About this activity

Test your knowledge of concepts related to artificial intelligence and machine learning.

Created by

LEELANANDHA KISHORE K S BTech_AIML
LEELANANDHA KISHORE K S BTech_AIML
India

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THE ML Mind Maze
 

Crossword Puzzle

THE ML Mind MazeOnline version

Test your knowledge of concepts related to artificial intelligence and machine learning.

by LEELANANDHA KISHORE K S BTech_AIML
1

A step-by-step procedure used for calculations and data processing.

2

A collection of data used to train and test machine learning models.

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A trained representation used by ML systems to make predictions.

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The process of teaching a model by feeding it data.

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Evaluating a trained model's performance using new data.

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The ratio of correctly predicted positive observations to total predicted positives.

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The ratio of correctly predicted positives to all actual positives.

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A type of ML that predicts continuous numerical values.

9

A type of ML that assigns inputs to discrete categories.

10

An unsupervised learning method to group similar data points.

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The target output that the model is expected to predict.

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An individual measurable property or characteristic of the data.

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The percentage of total predictions the model got correct.

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One complete cycle through the entire training dataset.

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A measure of how far the predicted output is from the actual result.

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A model that splits data based on decision rules to make predictions.

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A structure made up of interconnected neurons in deep learning.

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Quantitative measures to evaluate the performance of ML models.

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Refers to 'learning rate', which controls the speed of learning.

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Internal model variables (like weights) adjusted during training.

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A situation where the model learns the training data too well and fails to generalize.

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A condition where the model is too simple to learn from the data.

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An error due to overly simplistic assumptions in the learning algorithm.

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Error from sensitivity to small fluctuations in the training dataset.

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A regularization technique where some neurons are randomly turned off during training.

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Learning method using labeled data to train models.

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Learning method that deals with data without labeled responses.

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Learning based on rewards and penalties for actions.

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A network of nodes inspired by the human brain, used for pattern recognition.

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A table used to evaluate the performance of a classification model.

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A method to assess the performance of a model by partitioning the data.

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Technique to prevent overfitting by adding a penalty to the loss function.

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Short for Machine Learning, a field that enables systems to learn from data.

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Artificial Intelligence, the broader field that includes ML and cognitive computing.

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A subset of ML using multi-layered neural networks for complex tasks.

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Configuration values set before training that influence model performance.

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Function that introduces non-linearity in a neural network.

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An algorithm for updating weights in a neural network via reverse propagation of error.

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A vector that guides how much and in which direction to update weights.

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The process of minimizing loss to improve model accuracy.

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