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January 21, 2025
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This course is part of Natural Language Processing Specialization
Instructors: Younes Bensouda Mourri
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197,690 already enrolled
(4,513 reviews)
Recommended experience
Intermediate level
Working knowledge of machine learning, intermediate Python experience including DL frameworks & proficiency in calculus, linear algebra, & stats
(4,513 reviews)
Recommended experience
Intermediate level
Working knowledge of machine learning, intermediate Python experience including DL frameworks & proficiency in calculus, linear algebra, & stats
Use logistic regression, naïve Bayes, and word vectors to implement sentiment analysis, complete analogies & translate words.
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In Course 1 of the Natural Language Processing Specialization, you will:
a) Perform sentiment analysis of tweets using logistic regression and then naïve Bayes, b) Use vector space models to discover relationships between words and use PCA to reduce the dimensionality of the vector space and visualize those relationships, and c) Write a simple English to French translation algorithm using pre-computed word embeddings and locality-sensitive hashing to relate words via approximate k-nearest neighbor search. By the end of this Specialization, you will have designed NLP applications that perform question-answering and sentiment analysis, created tools to translate languages and summarize text. This Specialization is designed and taught by two experts in NLP, machine learning, and deep learning. Younes Bensouda Mourri is an Instructor of AI at Stanford University who also helped build the Deep Learning Specialization. Łukasz Kaiser is a Staff Research Scientist at Google Brain and the co-author of Tensorflow, the Tensor2Tensor and Trax libraries, and the Transformer paper.
Learn to extract features from text into numerical vectors, then build a binary classifier for tweets using a logistic regression!
15 videos14 readings1 assignment1 programming assignment1 app item3 ungraded labs
Learn the theory behind Bayes' rule for conditional probabilities, then apply it toward building a Naive Bayes tweet classifier of your own!
13 videos12 readings1 assignment1 programming assignment1 ungraded lab
Vector space models capture semantic meaning and relationships between words. You'll learn how to create word vectors that capture dependencies between words, then visualize their relationships in two dimensions using PCA.
10 videos10 readings1 assignment1 programming assignment3 ungraded labs
Learn to transform word vectors and assign them to subsets using locality sensitive hashing, in order to perform machine translation and document search.
11 videos11 readings1 assignment1 programming assignment2 ungraded labs
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
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Vanderbilt University
Specialization
Google Cloud
Course
4,513 reviews
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19.09%
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Reviewed on Feb 11, 2023
I really enjoy and this course is exactly what I expect. It covers both practical and conceptual aspects greatly and I recommend everyone to enroll in this course to make their NLP foundations strong
Reviewed on Jan 9, 2024
Started off great, but I feel like the more advanced stuff could've been better explained. Regarding the exercises, I felt like the labs often gave too much information that made them all to easy.
Reviewed on Aug 16, 2020
Awesome. The lecture are very exciting and detailed, though little hard and too straight forward sometimes, but Youtube helped in Regression models. Other then that, I was very informative and fun.
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