•Trained a transformer encoder from scratch jointly in Python with a feedforward classifier to predict speech authorship achieving over 85% accuracy. •Pre-trained a GPT-like decoder from scratch for unsupervised learning in word prediction using Python, achieved perplexity metrics below 400 with a training dataset of less than 200 KB.