Coursera – Natural Language Processing Specialization 2024-3 – Downloadable

explanation

Natural Language Processing Specialization Natural language processing, or NLP. NLP uses several algorithms to understand and modify Adam’s language. This technology is widely used in the field of machine learning, where developers build models on which speech and language analysis works. Template Text discovers this and your insight into the text and sound business works to your advantage. By using this course and mastering these techniques, you can apply NLP to create your own. (the moment the question and answer period ends). Sentiment analysis helps you translate and summarize text. This tool, along with other NLP-based tools, is the top tier of the future artificial intelligence era.

This course will cover a variety of topics. Learn how to analyze emotions, complete similarities, and translate words using logical regression and Bayesian categories. You will then learn the use of intelligent programming and Hidden Markov models for automatic vocabulary correction, sentence completion, and word role recognition. We use LSTM networks and recurrent, dense neural networks from Siamese’s TensorFlow and Trax libraries for advanced sentiment analysis, text composition, and duplicate question detection for other topics in this course. Finally, you will learn about implementing advanced machine translation, text summarization, and FAQs for building chatbots. For reference, the instructor of this course is an artificial intelligence instructor at Stafford University and a member of the Google Brain research team.

What to learn

It uses logical regression Bayes classifier and word array to analyze the complete similarity of emotions and translate vocabulary.
Automatically corrects vocabulary, completes sentences, and recognizes the roles of words in speech using intelligent programming, Hidden Markov models and word embeddings.
Use repeatable, dense LSTM, Grus, and Siamese networks from TensorFlow and Trax libraries for advanced sentiment analysis and text authoring.
Build a chatbot using text summary and FAQ using causal relationships and dependencies between encryption and decryption words.

Specifications for the Natural Language Processing Specialty

Publisher: Coursera
Instructors: Young Bensouda Mourri, Łukasz Kaiser, Eddy Shyu
Language:English
Training level: Intermediate
Quantity: 4 courses
Course duration: 3 months, 10 hours per week

procedure

Natural Language Processing Specialization

precondition

Working knowledge of machine learning, intermediate Python experience including DL frameworks, and proficiency in calculus, linear algebra, and statistics.

image

Natural Language Processing Specialization

sample video

installation manual

Custom view after extraction to player.

Subtitles: English

Quality: 720p

Changes:

The 2020/10 version has an addition compared to the 2020/9 fourth section.

The 2021/10 version has 46 lessons and 48 hours more class time compared to the 2020/10 version.

* In the 2021/10 version, many of the videos, texts, and training files for courses 3 and 4 have been completely edited and are different from the previous version.

The 2024/4 version has a shorter duration of 1 hour and 8 minutes compared to the 2021/10 version.