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Natural Language Processing Specialization

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Course Features

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Duration

4 months

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Intermediate

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Effort

7 hours per week

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Teaching Type

Self Paced

Course Description

Natural Language Processing (NLP), uses algorithms to understand and modify human language. This technology is one the most widely used areas of machine-learning. AI will continue to grow, as will the need for professionals who can build models that analyze speech, language, uncover context patterns, and extract insights from text or audio. This Specialization will prepare you to create NLP applications that answer questions and analyze sentiment, translate text and build chatbots. These and other NLP apps will be key to the future transformation to AI-powered AI. This Specialization was created and taught by two experts in NLP and machine learning. Younes Bensouda Morri, an instructor of AI at Stanford University, is also responsible for the creation of the Deep Learning Specialization. Lukasz Kaiser, a staff researcher scientist at Google Brain, is the coauthor of Tensorflow and the Tensor2Tensor, Trax and Transformer libraries as well as the Transformer paper.

Course Overview

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International Faculty

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Instructor-Moderated Discussions

Skills You Will Gain

What You Will Learn

Use dynamic programming, hidden Markov models, and word embeddings to implement autocorrect, autocomplete & identify part-of-speech tags for words

Use encoder-decoder, causal, & self-attention to machine translate complete sentences, summarize text, build chatbots & question-answering

Use recurrent neural networks, LSTMs, GRUs & Siamese network in TensorFlow & Trax for sentiment analysis, text generation & named entity recognition

Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies & translate words

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