Building NLP Classifiers from Ground Up with C++ and Python Binding

Learn how to implement sentiment analysis from the ground up through this 27-minute conference talk that explores Natural Language Processing and machine learning techniques. Discover the core mechanics of sentiment analysis, including data processing, classification methodologies, and practical implementation details like data correction and tokenization. Master the mathematical and statistical foundations of the Naïve Bayes classifier while understanding how to build models from scratch using C++ with Python bindings. Delivered by computer science student and machine learning enthusiast Radosław Szewczyk from the Silesian University of Technology, gain hands-on insights into developing NLP classifiers through a combined approach of theoretical understanding and practical implementation.