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Machine Learning and Natural Language Processing

The projects in this repository were created while working on the course Machine Learning and Natural Language Processing for my postgraduate studies. They include the following:

  1. Supervised learning (Classification): examining different financial performance indicators of Greek companies and creating a classification model to identify those that will go bankrupt.

  2. CNN architecture: development of a CNN model to be used on the CIFAR-10 dataset. The development includes experimentation with different loss functions and a more complex model structure.

  3. Unsupervised learning (Clustering): development of deep learning models and clustering techniques to be used on the fashion-mnist dataset (https://github.com/zalandoresearch/fashion-mnist). Distinction between clustering of raw data and the use of high level feature values extracted using stacked autoencoders.

  4. NLTK Project (Creation of sentences and classification of movie reviews): Use of the Python NLTK library to create sentences using bigrams and trigrams. In addition, using the NLTK movie_reviews dataset, training a classifier to correctly classify positive and negative reviews.

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