In this 7-video course, learners can explore the concepts of language modeling, natural language processing (NLP), and sequence generation for NLP. Prominent machine learning modeling algorithms such as vanishing gradient problem, gated recurrent units (GRUs), and long short-term memory (LSTM) network are also covered. Key concepts studied in this course include language models, one of the most important parts of NLP. and how to implement NLP along with its essential components; learning the process and approach of generating sequence for NLP; and vanishing gradient problem implementation approaches to overcome the problem of taking longer times to achieve convergence. Then, learn about features and characteristics of GRUs used to resolve issues with vanishing gradient problems, and learn the problems and drawbacks of implementing short-term memory and LSTM as modeling solutions. In the concluding exercise, learners will review the essential components and prominent applications of language modeling and specify some of the solutions for vanishing gradient problems.