Über diesen Kurs

532,254 kürzliche Aufrufe
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Mittel“

You should take the first 2 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.

Ca. 14 Stunden zum Abschließen
Englisch
Untertitel: Englisch, Koreanisch

Was Sie lernen werden

  • Build natural language processing systems using TensorFlow

  • Process text, including tokenization and representing sentences as vectors

  • Apply RNNs, GRUs, and LSTMs in TensorFlow

  • Train LSTMs on existing text to create original poetry and more

Kompetenzen, die Sie erwerben

Natural Language ProcessingTokenizationMachine LearningTensorflowRNNs
Zertifikat zur Vorlage
Erhalten Sie nach Abschluss ein Zertifikat
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Mittel“

You should take the first 2 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.

Ca. 14 Stunden zum Abschließen
Englisch
Untertitel: Englisch, Koreanisch

Dozent

von

deeplearning.ai-Logo

deeplearning.ai

Lehrplan - Was Sie in diesem Kurs lernen werden

InhaltsbewertungThumbs Up91%(4,830 Bewertungen)Info
Woche
1

Woche 1

3 Stunden zum Abschließen

Sentiment in text

3 Stunden zum Abschließen
13 Videos (Gesamt 30 min), 4 Lektüren, 3 Quiz
13 Videos
Introduction1m
Word based encodings2m
Using APIs2m
Notebook for lesson 12m
Text to sequence3m
Looking more at the Tokenizer1m
Padding2m
Notebook for lesson 24m
Sarcasm, really?2m
Working with the Tokenizer1m
Notebook for lesson 33m
Week 1 Wrap up21
4 Lektüren
Check out the code!10m
Check out the code!10m
News headlines dataset for sarcasm detection10m
Check out the code!10m
1 praktische Übung
Week 1 Quiz
Woche
2

Woche 2

4 Stunden zum Abschließen

Word Embeddings

4 Stunden zum Abschließen
14 Videos (Gesamt 39 min), 7 Lektüren, 3 Quiz
14 Videos
Introduction2m
The IMBD dataset1m
Looking into the details4m
How can we use vectors?2m
More into the details2m
Notebook for lesson 110m
Remember the sarcasm dataset?1m
Building a classifier for the sarcasm dataset1m
Let’s talk about the loss function1m
Pre-tokenized datasets43
Diving into the code (part 1)1m
Diving into the code (part 2)2m
Notebook for lesson 35m
7 Lektüren
IMDB reviews dataset10m
Check out the code!10m
Check out the code!10m
TensorFlow datasets10m
Subwords text encoder10m
Check out the code!10m
Week 2 Wrap up10m
1 praktische Übung
Week 2 Quiz
Woche
3

Woche 3

3 Stunden zum Abschließen

Sequence models

3 Stunden zum Abschließen
10 Videos (Gesamt 16 min), 7 Lektüren, 3 Quiz
10 Videos
Introduction2m
LSTMs2m
Implementing LSTMs in code1m
Accuracy and loss1m
A word from Laurence35
Looking into the code1m
Using a convolutional network1m
Going back to the IMDB dataset1m
Tips from Laurence37
7 Lektüren
Link to Andrew's sequence modeling course10m
More info on LSTMs10m
Check out the code!10m
Check out the code!10m
Check out the code!10m
Exploring different sequence models10m
Week 3 Wrap up10m
1 praktische Übung
Week 3 Quiz
Woche
4

Woche 4

3 Stunden zum Abschließen

Sequence models and literature

3 Stunden zum Abschließen
14 Videos (Gesamt 27 min), 5 Lektüren, 3 Quiz
14 Videos
Introduction1m
Looking into the code57
Training the data2m
More on training the data1m
Notebook for lesson 18m
Finding what the next word should be2m
Example1m
Predicting a word1m
Poetry!40
Looking into the code1m
Laurence the poet!1m
Your next task1m
A conversation with Andrew Ng1m
5 Lektüren
Check out the code!10m
link to Laurence's poetry10m
Check out the code!10m
Link to generating text using a character-based RNN10m
Wrap up10m
1 praktische Übung
Week 4 Quiz

Bewertungen

Top-Bewertungen von NATURAL LANGUAGE PROCESSING IN TENSORFLOW

Alle Bewertungen anzeigen

Über den Spezialisierung TensorFlow in Practice

Discover the tools software developers use to build scalable AI-powered algorithms in TensorFlow, a popular open-source machine learning framework. In this four-course Specialization, you’ll explore exciting opportunities for AI applications. Begin by developing an understanding of how to build and train neural networks. Improve a network’s performance using convolutions as you train it to identify real-world images. You’ll teach machines to understand, analyze, and respond to human speech with natural language processing systems. Learn to process text, represent sentences as vectors, and input data to a neural network. You’ll even train an AI to create original poetry! AI is already transforming industries across the world. After finishing this Specialization, you’ll be able to apply your new TensorFlow skills to a wide range of problems and projects. Looking for more advanced TensorFlow content? Check out the new TensorFlow: Data and Deployment Specialization....
TensorFlow in Practice

Häufig gestellte Fragen

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

Haben Sie weitere Fragen? Besuchen Sie das Hilfe-Center für Teiln..