05
Δεκ
Σεμινάριο MATLAB – Πολυτεχνείο Κρήτης
Τετάρτη 05.12.2018, ώρες: 13:00-16:00, Αμφιθέατρο Επιστημών
Ομιλητής: Γκέτσης Ζαχαρίας
Machine Learning and Deep Learning with MATLAB
Importing and Organizing Data |
Objective: Bring data into MATLAB and organize it for analysis, including normalizing data and removing observations with missing values.
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Finding Natural Patterns in Data (Clustering) |
Objective: Use unsupervised learning techniques to group observations based on a set of explanatory variables and discover natural patterns in a data set.
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Building Classification Models |
Objective: Use supervised learning techniques to perform predictive modeling for classification problems. Evaluate the accuracy of a predictive model.
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Building Regression Models |
Objective: Use supervised learning techniques to perform predictive modeling for continuous response variables.
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Creating Neural Networks |
Objective: Create and train neural networks for clustering and predictive modeling. Adjust network architecture to improve performance.
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Transfer Learning for Image Classification |
Objective: Perform image classification using pretrained networks. Use transfer learning to train customized classification networks.
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Building Convolutional Networks |
Objective: Build convolutional networks from scratch. Understand how information is passed between network layers and how different types of layers work. Train networks to locate and label specific objects within images.
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