About this Course

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Intermediate Level

Working knowledge of machine learning, intermediate Python experience including DL frameworks & proficiency in calculus, linear algebra, & stats

Approx. 31 hours to complete
English

What you will learn

  • Use dynamic programming, hidden Markov models, and word embeddings to implement autocorrect, autocomplete & identify part-of-speech tags for words.

Skills you will gain

  • Word2vec
  • Parts-of-Speech Tagging
  • N-gram Language Models
  • Autocorrect
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Intermediate Level

Working knowledge of machine learning, intermediate Python experience including DL frameworks & proficiency in calculus, linear algebra, & stats

Approx. 31 hours to complete
English

Offered by

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DeepLearning.AI

Syllabus - What you will learn from this course

Content RatingThumbs Up91%(5,601 ratings)Info
Week
1

Week 1

7 hours to complete

Autocorrect

7 hours to complete
11 videos (Total 31 min), 10 readings, 3 quizzes
Week
2

Week 2

6 hours to complete

Part of Speech Tagging and Hidden Markov Models

6 hours to complete
13 videos (Total 43 min), 11 readings, 3 quizzes
Week
3

Week 3

9 hours to complete

Autocomplete and Language Models

9 hours to complete
11 videos (Total 54 min), 9 readings, 3 quizzes
Week
4

Week 4

9 hours to complete

Word embeddings with neural networks

9 hours to complete
22 videos (Total 73 min), 21 readings, 3 quizzes

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About the Natural Language Processing Specialization

Natural Language Processing

Frequently Asked Questions

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