The book offers comprehensive coverage of the most essential topics, including:
* Programmatically reading and manipulating image data
* Extracting relevant features from images
* Building statistical models using image features
* Using state-of-the-art Deep Learning models for feature extraction
* Build a robust phishing detection tool even with less data
* Dimensionality reduction techniques
* Class imbalance treatment
* Feature Fusion techniques
* Building performance metrics for multi-class classification task
Another unique aspect of this book is it comes with a completely reproducible code base developed by the author and shared via python notebooks for quick launch and running capabilities. They can be leveraged for further enhancing the provided models using new advancement in the field of computer vision and more advanced algorithms.