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A very good type of machine learning problem is handwritten digit recognition. Intel DAAL does a good job at solving this problem by providing several relevant application algorithms such as Support Vector Machine (SVM), Principal Component Analysis (PCA), Naïve Bayes, and Neural Networks. Below there is an example that uses SVM to solve this problem.
Recognition is essentially the prediction or inference stage in the machine learning pipeline.In simple words, When given a handwritten digit, the system should be able to recognize or infer what determine which digit was had been written. For In order for a system to be able to predict the output with a given inputset of data, it needs a trained model learned from the training data set that provides would provide the system with the capability to make an inference or a calculated prediction. The first step before constructing a training model is to collect training datafrom the given data within the .csv data set files
=== Loading Data in Intel DAAL ===
=== Training Data in Intel DAAL ===
[[File:trainpic.jpg]]</br>
Initialize FileDataSource<CSVFeatureManager> to retrieve input data from .csv file
<source lang=c++>
=== Testing The Trained Model ===
[[File:testpic.jpg]]</br>
Initialize testDataSource to retrieve test data from a .csv file
<source lang=c++>