How to Create a Facebook Business Page: Step-By-Step Guide
November 29, 2023
Article
This course is part of Natural Language Processing Specialization
Instructors: Younes Bensouda Mourri
Instructor ratings
We asked all learners to give feedback on our instructors based on the quality of their teaching style.
198,490 already enrolled
(4,517 reviews)
Recommended experience
Intermediate level
Working knowledge of machine learning, intermediate Python experience including DL frameworks & proficiency in calculus, linear algebra, & stats
(4,517 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.
Add to your LinkedIn profile
4 assignments
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
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.
DeepLearning.AI is an education technology company that develops a global community of AI talent. DeepLearning.AI's expert-led educational experiences provide AI practitioners and non-technical professionals with the necessary tools to go all the way from foundational basics to advanced application, empowering them to build an AI-powered future.
DeepLearning.AI
Course
DeepLearning.AI
Specialization
DeepLearning.AI
Course
DeepLearning.AI
Course
4,517 reviews
73.88%
19.08%
4.51%
1.28%
1.23%
Showing 3 of 4517
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 Dec 8, 2020
Very structured and clear instructions but not as detail as Andrew Ng's ML course. But still great starting point for those pursuing NLP. So far the most decent NLP tutorial online.
Reviewed on Jul 11, 2020
Best Course Content for begginers as this course begins code with Scratch and popluates code with basic operations. In my opinion, this is the best course for NLP. Thanks Instructors
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.