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Inicio 4 June 2026 10:02
Fin 4 June 2026
Natural Language Processing with Probabilistic Models
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Resumen
Embark on a transformative journey with the "Natural Language Processing with Probabilistic Models" course, the second installment in the renowned Natural Language Processing Specialization offered through Coursera. This comprehensive course empowers you to:
- Develop a practical auto-correct tool by leveraging minimum edit distance and dynamic programming.
- Master the application of the Viterbi Algorithm for accurate part-of-speech tagging, a cornerstone of computational linguistics.
- Enhance your skills in crafting advanced auto-complete algorithms using the powerful N-gram language model.
- Innovate with your very own Word2Vec model, employing a neural network to generate meaningful word embeddings through a continuous bag-of-words approach.
By completing this specialization, you'll gain the expertise to create NLP applications capable of question-answering and sentiment analysis, devise language translation and text summarization tools, and even design a sophisticated chatbot.
This specialization is meticulously crafted by NLP, machine learning, and deep learning luminaries, Younes Bensouda Mourri and Łukasz Kaiser. Mourri, a distinguished Instructor of AI at Stanford University and a contributor to the Deep Learning Specialization, joins forces with Kaiser, a Staff Research Scientist at Google Brain, co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the seminal Transformer paper.
Dive into the realms of Natural Language Processing (NLP), Sentiment Analysis, and more with this cutting-edge course, available now on Coursera.
Impartido por
Younes Bensouda Mourri, Łukasz Kaiser and Eddy Shyu
