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Отзывы учащихся о курсе Sequences, Time Series and Prediction от партнера deeplearning.ai

4.7
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Оценки: 4,528

О курсе

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In this fourth course, you will learn how to build time series models in TensorFlow. You’ll first implement best practices to prepare time series data. You’ll also explore how RNNs and 1D ConvNets can be used for prediction. Finally, you’ll apply everything you’ve learned throughout the Specialization to build a sunspot prediction model using real-world data! The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization....

Лучшие рецензии

OR

3 авг. 2019 г.

It was an amazing experience to learn from such great experts in the field and get a complete understanding of all the concepts involved and also get thorough understanding of the programming skills.

MI

6 июня 2020 г.

I really enjoyed this course, especially because it combines all different components (DNN, CONV-NET, and RNN) together in one application. I look forward to taking more courses from deeplearning.ai.

Фильтр по:

126–150 из 716 отзывов о курсе Sequences, Time Series and Prediction

автор: Seunghye W

16 сент. 2020 г.

Great course for review and hands-on practice of RNN/LSTM/DNN after AI specialization (Sequence Models). However, without background of DL (sequence models) it's a bit hard to catch up.

автор: Reinier V

15 янв. 2021 г.

Good introduction to time series (or a recap). Much more applied than the previous courses. If considering only 1 of the courses in this specialization I would do the time series one!

автор: Priscilla V A

25 апр. 2021 г.

The course is overall amazing, the notebooks and videos given go hand in hand to build student's understanding. However, the video sound is too soft, using high volume is recommended

автор: Giuseppe S

3 мая 2020 г.

Great introduction to Time series forecasting using neural networks. I liked the journey from statistics-based approaces to DL. And the application to sunspots was very interesting

автор: Mehmet B

9 июля 2020 г.

An exceptional course design to enable practicing with ready code and teaching what actually runs in LSTM / DNN models. With this momentum, anyone will continue on another course.

автор: Chidvilas K R

28 окт. 2020 г.

This is probably the only course worth taking in this specialization. The first three were very basic while this one really went a bit deep. It was really fun taking this course.

автор: Taniya S

4 авг. 2020 г.

Great course with good in-depth knowledge of implementation of Tensorflow in sequence models. thank you for the courses and I look forward to complete more courses to learn more.

автор: Cihan T

13 дек. 2020 г.

Really enjoyed the course. I think the content and style are both concise and spot-on to get the key materials. Learning more is up to the students. Thanks for all your effort!

автор: Dishant T

16 февр. 2021 г.

Excellent course, I loved the final sunspot activity forecasting project because I learned about the steps that one should follow in order to get towards more accurate models.

автор: Hsin-Ying C

11 апр. 2020 г.

I really enjoyed it. This is exactly what we need as the first step of machine learning in patice, to see it in action. I am going to dive deeper into Andrew's specialization.

автор: bryan m

11 апр. 2020 г.

It really help to start using tensorflow in the time series prediction data, i was hopping at least one example of multivariate data, but other than that it was really helpful

автор: Erdem Ç

8 июля 2020 г.

Precise and to the point introduction of topics and a really nice head start into practical aspects of Time Series and Sequences and using the amazing tensorflow framework.

автор: Colman S

1 дек. 2019 г.

Great introduction to TensorFlow. Very broad coverage of the tools available in TensorFlow for Machine learning. Everything you need to get started on your first project!

автор: DaesooLee

9 мая 2020 г.

Short, concise, and practical. But maybe, it'd be better if some more practical examples are addressed that clearly shows the power of the (CNN-)LSTM model over DNN.

автор: Zhi L

16 апр. 2022 г.

very resourceful course indeed, learnt a lot about the workflow of model development with time series datasets, and how to make trade-offs on hyperparameter tuning.

автор: Marco D V

25 нояб. 2020 г.

Great courses! Please do not evaluate this course as it is ! You need to take also the ML and Deep Learning previous courses before find the real taste of this one!

автор: Anjana K V

26 нояб. 2019 г.

Thank you Laurence sir and Andrew sir for putting together this course. It gives a good foundation to learn more about deep learning and its numerous applications.

автор: Gurpreet S

5 авг. 2019 г.

Fantastic course, starting from basic fundamentals of statistical forecasting to using Convolutional neural networks. I will use my learnings directly to my job.

автор: santiago r z

18 нояб. 2020 г.

Great courses made by great people. Every course shows how to nicely handle practical problems that need to be solved when implementing Deep Learning algorithm.

автор: Shreyansh G

21 февр. 2021 г.

There should be more explanation on why the convolution layer was used in the time series predictions and an explanation of time series data generation code.

автор: Olena I

25 окт. 2020 г.

Quite interesting and useful course. I wish there is more theory on LSTM embedded INTO the course, and not given as a reference to another course. Thank you!

автор: SMRUTI R D

22 июля 2020 г.

The practice problems could have been a bit more rigorous. you may think of prediction of stock prices as an exercise. Thanks a lot for this specialization..

автор: renzo a g

7 янв. 2022 г.

Realmente quisiera agradecer al equipo por el gran trabajo que hay detrás de este curso. Se hace bastante fluido avanzar, solo basta con tener las ganas!