In this Natural Language Processing (NLP) course, you will learn how to create a simple auto-correct algorithm using minimum edit distance and programming, apply the Viterbi Algorithm for part-of-speech (POS) tagging, write an improved auto-complete algorithm using an N-gram language model and also your own Word2Vec model using a neural network to compute word embeddings.
🆓 Free to Audit
🕒 Approx. 31 Hours
📈 Intermediate Level
🧾 Paid Certificate Available Upon Completion
🎓 Offered by DeepLearning.AI via Coursera
