About this Course

339,390 recent views
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 29 hours to complete
English

Skills you will gain

Machine TranslationWord EmbeddingsLocality-Sensitive HashingSentiment AnalysisVector Space Models
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level
Approx. 29 hours to complete
English

Offered by

Placeholder

DeepLearning.AI

Syllabus - What you will learn from this course

Content RatingThumbs Up97%(10,104 ratings)Info
Week
1

Week 1

9 hours to complete

Sentiment Analysis with Logistic Regression

9 hours to complete
13 videos (Total 84 min), 13 readings, 1 quiz
13 videos
Welcome to Course 11m
Supervised ML & Sentiment Analysis2m
Vocabulary & Feature Extraction2m
Negative and Positive Frequencies2m
Feature Extraction with Frequencies2m
Preprocessing3m
Putting it All Together2m
Logistic Regression Overview3m
Logistic Regression: Training1m
Logistic Regression: Testing4m
Logistic Regression: Cost Function5m
Andrew Ng with Chris Manning46m
13 readings
Connect with your mentors and fellow learners on Slack!10m
Acknowledgement - Ken Church10m
Supervised ML & Sentiment Analysis2m
Vocabulary & Feature Extraction2m
Feature Extraction with Frequencies10m
Preprocessing10m
Putting it all together10m
Logistic Regression Overview10m
Logistic Regression: Training10m
Logistic Regression: Testing10m
Optional Logistic Regression: Cost Function10m
Optional Logistic Regression: Gradient10m
How to refresh your workspace10m
Week
2

Week 2

7 hours to complete

Sentiment Analysis with Naïve Bayes

7 hours to complete
11 videos (Total 40 min), 11 readings, 1 quiz
11 videos
Bayes’ Rule3m
Naïve Bayes Introduction5m
Laplacian Smoothing2m
Log Likelihood, Part 15m
Log Likelihood, Part 21m
Training Naïve Bayes3m
Testing Naïve Bayes4m
Applications of Naïve Bayes3m
Naïve Bayes Assumptions3m
Error Analysis3m
11 readings
Probability and Bayes’ Rule10m
Bayes' Rule10m
Naive Bayes Introduction10m
Laplacian Smoothing10m
Log Likelihood, Part 110m
Log Likelihood Part 210m
Training naïve Bayes10m
Testing naïve Bayes10m
Applications of Naive Bayes10m
Naïve Bayes Assumptions10m
Error Analysis10m
Week
3

Week 3

6 hours to complete

Vector Space Models

6 hours to complete
8 videos (Total 26 min)
8 videos
Word by Word and Word by Doc. 4m
Euclidean Distance3m
Cosine Similarity: Intuition2m
Cosine Similarity3m
Manipulating Words in Vector Spaces3m
Visualization and PCA3m
PCA Algorithm3m
Week
4

Week 4

6 hours to complete

Machine Translation and Document Search

6 hours to complete
9 videos (Total 65 min), 2 readings, 1 quiz
9 videos
Transforming word vectors6m
K-nearest neighbors3m
Hash tables and hash functions3m
Locality sensitive hashing5m
Multiple Planes3m
Approximate nearest neighbors3m
Searching documents1m
Andrew Ng with Kathleen McKeown35m
2 readings
Acknowledgements10m
Bibliography10m

Reviews

TOP REVIEWS FROM NATURAL LANGUAGE PROCESSING WITH CLASSIFICATION AND VECTOR SPACES

View all reviews

About the Natural Language Processing Specialization

Natural Language Processing

Frequently Asked Questions

More questions? Visit the Learner Help Center.