Machine learning (ML) has enabled a whole host of innovations and new business models in fintech, driving breakthroughs in areas such as personalized wealth management, automated fraud detection, and real-time small business accounting tools. For a long time, one of the most significant challenges of machine learning has been the amount and quality of data that is required to train machine learning models. Recent developments of Transformer architectures, however, have started to change this equation. Transformer-based models like BERT (Bidirectional Encoder Representations from Transformers, developed at Google) and GPT (Generative Pre-Training, developed at OpenAI) have brought about the biggest changes in machine learning in recent years. These technologies were initially developed to process natural language data but are now creating exciting new opportunities across many applications, including fintech. Want to learn the fundamental building blocks of Data Modeling?