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Deep Learning
Deep learning allows a machine to independently mimic human
thought patterns. It is a subset of machine learning.
Training and Testing Data
Training and testing data are crucial components in machine learning. The training data is used
to teach the model by allowing it to learn patterns, relationships, and behaviors from the input
data. Once the model has been trained, the testing data, which is kept separate from the training
set, is used to evaluate the model’s performance and its ability to generalise to unseen data.
Training Data
Training data is a collection of labelled information that is used to build a machine learning
model. It can be annotated text, images, videos or audios. Through training data, an AI model
learns to perform its task with high-level of accuracy.
Test Data
The data that is given to an AI machine to test the machine is called test data. Based on the
training data the AI-enabled machine predicts the output from the test data.
Training Data
Prediction
Video
TXT
TXT TXT Text
Model Training
Lables TXT
Test Data
Video TXT Audio
Text
Pattern Recognition
Pattern recognition is a data analysis method that uses
machine learning algorithms to automatically recognise
patterns and regularities in data. This data can be anything
from text and images to sounds or other definable
qualities. Pattern recognition systems can recognise
familiar patterns quickly and accurately.
154 TrackGPT iPRO (V5.0)-VII

