Description
Natural Language Processing Specialization is a natural language processing or NLP training course. NLP uses several algorithms to understand and change human language. This technology is widely used in the field of machine learning. Developers use it to build models that analyze speech and language, discover text patterns, and gain insight from text and audio. By using this training course and mastering this technology, you are able to create your own NLP applications. Applications that deal with questions and answers, analyze emotions and are able to translate and summarize the text. This tool, along with other NLP-based tools, are considered the highest layer in the future era of artificial intelligence.
This course covers a variety of topics. You will learn how to use logistic regression and Bayesian classifiers for sentiment analysis, similarity completion, and word translation. Then you will learn to use intelligent programming and hidden Markov models to automatically correct words, complete sentences and recognize the role of words. The use of recurrent, dense and LSTM neural networks in TensorFlow and Trax libraries for more advanced sentiment analysis, text creation and recognition of repetitive questions are other topics of this course. At the end, you will learn about the implementation of advanced machine translation, text summarization, and questions and answers to build a chat bot. It should be noted that the lecturers of this course are artificial intelligence lecturers at Stanford University and members of the research team at Google Brain.
What do you learn:
- Using logical regression, Bayes classifier and an array of words. Analyzing emotions, completing similarities and translating words
- Using intelligent programming, hidden Markov models and embedding words. Automatic correction of words, completion of sentences and recognition of the role of words in speech
- Using recurrent neural networks, dense, LSTM, GRUs and Siamese network in TensorFlow and Trax libraries. More advanced sentiment analysis and text construction
- Using encoding and decoding, causal relationships and dependence between words. Summarizing the text and questions and answers to build a Chatbot
Characteristics of the Natural Language Processing Specialization training set:
- Publisher: Coursera
- teacher : Younes Bensouda Mourri , Łukasz Kaiser , Eddy Shyu
- English language
- Education level: Intermediate
- Number: 4 courses
- Duration of the course: with a suggested time of 10 hours per week, approximately 3 months
courses
Natural Language Processing Specialization prerequisites
Working knowledge of machine learning, intermediate Python experience including DL frameworks & proficiency in calculus, linear algebra, & statistics.
Pictures
Natural Language Processing Specialization sample video
Installation guide
After extracting, watch with your favorite player.
English subtitle
Quality: 720p
Changes:
Version 2020/10 compared to 2020/9, the fourth section was added.
The 2021/10 version has increased the number of 46 lessons and the duration of 48 hours compared to 2020/10.
* In the 2021/10 version, a number of videos and text and exercise files of the third and fourth courses have been completely edited and are different from the old versions.
Version 2024/4 compared to 2021/10, the duration has decreased by 1 hour and 8 minutes.
download link
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): www.downloadly.ir
Size
2.06 GB
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