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Natural Language Processing with Classification and Vector Spaces

In Course 1 of the Natural Language Processing Specialization, offered by deeplearning.ai, you will: a) Perform sentiment analysis of tweets using logistic...
4.6
4.6/5
(2,818 reviews)
81,731 students
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8.8

Classbaze Grade®

N/A

Freshness

8.4

Popularity

8.7

Material

Natural Language Processing with Classification and Vector Spaces
Platform: Coursera
Video: 3h 35m
Language: English

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8.8 / 10

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8.4 / 10
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Material

8.7 / 10
Video Score: 8.1 / 10
The course includes 3h 35m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 5 hours 48 minutes of 749 Machine Learning courses on Coursera.
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Extra Content Score: 9.8 / 10

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This course contains:

41 articles.
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4 tests or quizzes.

In this page

About the course

In Course 1 of the Natural Language Processing Specialization, offered by deeplearning.ai, 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.

Please make sure that you’re comfortable programming in Python and have a basic knowledge of machine learning, matrix multiplications, and conditional probability.

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, and even built a chatbot!

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.

What can you learn from this course?

What you need to start the course?

Basic knowledge of Machine Learning is required to start this course, as this is an intermediate level course.

Who is this course is made for?

This course was made for intermediate-level students.

Are there coupons or discounts for Natural Language Processing with Classification and Vector Spaces ? What is the current price?

Access to most course materials is FREE in audit mode on Coursera. If you wish to earn a certificate and access graded assignments, you must purchase the certificate experience during or after your audit.

If the course does not offer the audit option, you can still take a free 7-day trial.
The average price is $13.6 of 749 Machine Learning courses. So this course is 100% cheaper than the average Machine Learning course on Coursera.

Will I be refunded if I'm not satisfied with the Natural Language Processing with Classification and Vector Spaces course?

Coursera offers a 7-day free trial for subscribers.

Are there any financial aid for this course?

YES, you can get a scholarship or Financial Aid for Coursera courses. The first step is to fill out an application about your educational background, career goals, and financial circumstances. Learn more about financial aid on Coursera.

Who will teach this course? Can I trust Younes Bensouda Mourri?

Younes Bensouda Mourri has created 5 courses that got 861 reviews which are generally positive. Younes Bensouda Mourri has taught 90,782 students and received a 4.65 average review out of 861 reviews. Depending on the information available, we think that Younes Bensouda Mourri is an instructor that you can trust.
Instructor of AI, Stanford University
DeepLearning.AI
Younes completed his Bachelor’s in Applied Mathematics and Computer Science and Master’s in Statistics from Stanford University. Younes helped create 3 AI courses at Stanford – Applied Machine Learning, Deep Learning, and Teaching AI – and taught two of them for a few years. He also helped create the Deep Learning Specialization offered by deeplearning.ai on Coursera.

8.8

Classbaze Grade®

N/A

Freshness

8.4

Popularity

8.7

Material

Platform: Coursera
Video: 3h 35m
Language: English

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