Chevron Left
返回到 Sequence Models for Time Series and Natural Language Processing

Sequence Models for Time Series and Natural Language Processing, Google 云端平台

4.5
118 个评分
15 个审阅

课程信息

***NEW! Specialization Completion Challenge, receive Qwiklabs credits valued up to $150! See below for details.*** This course is an introduction to sequence models and their applications, including an overview of sequence model architectures and how to handle inputs of variable length. • Predict future values of a time-series • Classify free form text • Address time-series and text problems with recurrent neural networks • Choose between RNNs/LSTMs and simpler models • Train and reuse word embeddings in text problems You will get hands-on practice building and optimizing your own text classification and sequence models on a variety of public datasets in the labs we’ll work on together. Prerequisites: Basic SQL, familiarity with Python and TensorFlow SPECIALIZATION COMPLETION CHALLENGE As if learning new skills wasn’t enough of an incentive, we're excited to announce a special completion challenge for 'Advanced Machine Learning with TensorFlow on GCP’ specialization. Here’s how it works: Our completion challenge runs through 11:59pm PT May 5, 2019. Complete any course in this Specialization including this one, anytime in this period and we'll send you 30 Qwiklabs credits for each course completed (upto $150 value given there are 5 courses in the specialization). You can use these credits to take additional labs and earn badges, which you can then add to your resume and social profiles. Your challenge awaits – begin learning on Coursera today!...

热门审阅

创建者 JW

Nov 11, 2018

Excellent course for those who know RNN. Knowledge is refreshed and techniques are consolidated. More details about Google ecosystem is introduced.

创建者 MD

Feb 03, 2019

Very good.The explanation of the RNN was very good but the tensor2tensor was very hard.

筛选依据:

15 个审阅

创建者 Nguyễn Văn Long

Apr 14, 2019

pretty great

创建者 vincent poncet

Feb 24, 2019

Several exercices do not work as described, with error messages.

Explanations of what we are doing are light.

创建者 Yunwei Hu

Feb 20, 2019

Too focused on GCP. Could be more on DL itself.

创建者 Carlos Viejo

Feb 03, 2019

Excellent Sequence Models explanations and examples to learn from, I quite enjoyed all the fantastic tips and best practices recommended by Google, looking forward to the next course in the specialization.

创建者 Mark Davey

Feb 03, 2019

Very good.The explanation of the RNN was very good but the tensor2tensor was very hard.

创建者 ELINGUI Pascal Uriel

Jan 27, 2019

Great one!

创建者 Arindam Ghoshal

Dec 20, 2018

No Doubt COURSERA is always best AND MNC like IBM,Google courses associated with coursera are MIND-BLOWING.

The Instructors are so great at Explanation Part that hardly anyone won't Understand All the Topics

I would love to thank all the INSTRUCTORS who created such a Awesome Content for us.

My Personal Ratings For All the Instructors: 100 / 100

创建者 Raja Ranjith Garikapati

Dec 11, 2018

Good

创建者 Elias Papachristos

Dec 04, 2018

I really loved it!

创建者 Hemant Devidas Kshirsagar

Dec 01, 2018

Very informative, very much useful to my ongoing work on NLP.