Word2Vec: Build Semantic Recommender System with TensorFlow faq

star-rating
2.9
learnersLearners: 159
instructor Instructor: GoTrained AcademyIman Nazari instructor-icon
duration Duration: duration-icon

Learn how to build a semantic recommender system with TensorFlow using Word2Vec, and solve your problem of creating a powerful recommendation engine with a proven promise, backed by proof of successful implementations.

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Course Feature Course Overview Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Paid

providerProvider:

Udemy

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

2018-12-07

Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [August 31st, 2023]

What does this course tell?
(Please note that the following overview content is from Alison)
This Word2Vec tutorial will teach you how to use a Word2Vec Python model to semantically suggest names based on one or two given names. Word2vec is a group of related models that create Word Embeddings, which are vector representations of a particular word. This tutorial will cover the idea behind Word2Vec, how to implement it in Python TensorFlow, and how to use the model to suggest names.

We consider the value of this course from multiple aspects, and finally summarize it for you from three aspects: personal skills, career development, and further study:
(Kindly be aware that our content is optimized by AI tools while also undergoing moderation carefully from our editorial staff.)
What skills and knowledge will you acquire during this course?
In this Word2Vec tutorial, students will acquire the skills and knowledge to build a semantic recommender system with TensorFlow. They will learn the concept of word embeddings and how to implement it in Python using the TensorFlow library. They will also learn how to pre-process, tokenize, batch, structure, and train a Word2Vec Python model. Finally, they will use the trained model to semantically suggest names based on one or two given names.
lHow does this course contribute to professional growth?
This Word2Vec tutorial is an excellent opportunity for professionals to gain a better understanding of the Word2Vec algorithm and its implementation in Python and TensorFlow. By completing this course, professionals will be able to build and train a Word2Vec Python model and use it to semantically suggest names based on one or even two given names. This will help professionals to develop their skills in data science and machine learning, and will also help them to stay up-to-date with the latest trends in the field.

Is this course suitable for preparing further education?
Yes, this course is suitable for preparing further education as it provides an in-depth understanding of the Word2Vec algorithm and how to implement it using the Python library TensorFlow. It also provides a practical example of how to use the Word2Vec model to semantically suggest names based on one or two given names.

Course Syllabus

Course Overview

Model Building and Training

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faq FAQ for Tensorflow Courses

Q1: Does the course offer certificates upon completion?

Yes, this course offers a paid certificate. AZ Class have already checked the course certification options for you. Access the class for more details.

Q2: How do I contact your customer support team for more information?

If you have questions about the course content or need help, you can contact us through "Contact Us" at the bottom of the page.

Q3: How many people have enrolled in this course?

So far, a total of 159 people have participated in this course. The duration of this course is hour(s). Please arrange it according to your own time.

Q4: How Do I Enroll in This Course?

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