Coursera – Natural Language Processing Specialization 2024-3 – Download
Description
Specializing in natural language processing is a Natural Language Processing or NLP course. NLP uses several algorithms to understand and modify Adam’s language. This technology is widely used in the field of machine learning and its developers build models for speech and language analysis. The template text will recognize it, and insight into the text and solid business work will benefit from it. By using this course and mastering this technology, you will be able to make the application of NLP your own; the moment the question and answer period begins). You are able to translate and summarize the text. This tool, along with other NLP-based tools, is the highest level in the future era of artificial intelligence.
This course covers various topics. You’ll learn how to use logical regression and Bayesian categories to analyze emotions, complete similarities, and translate words. You will then learn how to use intelligent programming and hidden Markov models for automatic vocabulary correction, sentence completion and word roll recognition. The use of iterative and dense neural networks, e.g. B. the LSTM network and the Siamese libraries TensorFlow and Trax, for more advanced emotion analysis, text construction and duplicate question detection from other topics in this course. Finally, you will familiarize yourself with the implementation of advanced machine translation, text summarization and FAQ to build the chatbot. It should be noted that the lecturers of this course are artificial intelligence lecturers at Stafford University and members of the Google Brain research team.
What things to learn
Use the Bayesian categorizer with logical regression and a set of words to analyze emotions, complete similarities and vocabulary
Use intelligent programming, hidden Markov models, and word embedding to automatically correct vocabulary, complete sentences, and recognize the role of words in language
Use repeatable, dense LSTM, Grus, and Siamese networks in TensorFlow and Trax libraries for advanced emotion analysis and text creation.
Use encryption and decryption, causal relationships and dependencies between words to summarize text and FAQ to create a chatbot
Specifications of the Natural Language Processing specialization
Publisher: Coursera
Lecturers: the young Bensouda Mourri, Łukasz Kaiser, Eddy Shyu
Language: English
Education level: intermediate
Quantity: 4 courses
Duration of the course: 3 months of 10 hours per week
Courses
requirements
- Basic knowledge of machine learning, advanced Python experience including DL frameworks and knowledge of calculus, linear algebra and statistics.
Pictures
Example film
installation Guide
After extracting with the player you will get your custom view.
Subtitles: English
Quality: 720p
Changes:
The 2020/10 version was added compared to the fourth section 2020/9.
The 2021/10 version has increased by 46 lessons and a duration of 48 hours compared to 2020/10.
* In the 2021/10 version, some videos as well as text and training files for courses three and four have been completely revised and differ from the old versions.
Version 2024/4 compared to 2021/10, the duration has decreased by 1 hour and 8 minutes.
Download links
Natural Language Processing with Attention Models 2024-3
Natural Language Processing with Classification and Vector Spaces 2024-3
Natural Language Processing with Probabilistic Models 2024-3
Natural Language Processing with Sequence Models 2024-3
Password file(s): free software
File size
2.3GB