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Вернуться к Sequences, Time Series and Prediction

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

4.7
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Оценки: 4,240
Рецензии: 677

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.

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76–100 из 679 отзывов о курсе Sequences, Time Series and Prediction

автор: Tibor K

11 сент. 2020 г.

It was really refreshing to watch the recommended methods, but I think I have found a much better method for time series forecasting. In the next days I will compare what I have learned here with what I did by myself using Koopman operator based methods.

автор: PRANAV S D

3 окт. 2019 г.

The concepts from Deep Learning specialization by Prof. Andrew has explained well here for Keras. I expected graded programming assignments from scratch. Similar material you can find on internet but here it is very well compiled, organized, authentic.

автор: Petyo P

17 апр. 2020 г.

LOVE IT!

This course was a great investent of time and money. It was time efficient and gave a lot of information. I am fully motivated now to go into the Deep Learnign Specialization and to participate in futura specializations from these instructors.

автор: Rehan U

12 мая 2020 г.

It's been a spectacular specialization with lots of hands-on practice. This Specialization has been one-stop for all the things to learn from TensorFlow.

Thanks to Laurence and Andrew🤗.

Looking forward for learn more exciting things from you✌✌

автор: Ibrahim O

3 сент. 2019 г.

It has been a great time putting time into this specialization there is still more to learn which I know you guys will always try your best to release more courses that will comprehend what we've learned in this specialization.

Thank you all.

автор: Louis C

13 авг. 2021 г.

Very clear explanations, no useless content, esay to use notebooks and a focus on practical implementation and use which is appreciated.

What's more, links to more theoretical content is provided, which gives a nice complement to the course.

автор: Alfredo C

9 мая 2021 г.

Explanations are quite clear, and the examples are useful to understand how to apply different concepts. This course is helpful, after taking courses on deep learning and being familiar with concepts like LSTM, CNN, dense layers, and so on.

автор: MD. A K A

5 мая 2020 г.

This course helped me to learn Time Series in the same way a machine learns from data. Without having much theoretical knowledge, now I can run basic models. Thanks a lot to deeplearning.ai team for proving such a practical oriented course.

автор: Tharindu B A

15 авг. 2019 г.

This course is amazing and above my expectations! Very good exercises, good speed, well communicated. The instructor made me feel very comfortable and was able to take many things away. Excellent content and very knowledgeable instructor!

автор: Carlos V

6 окт. 2019 г.

Fantastic explanations and techniques to use CNN and RNN to predict time series, I learned quite a lot by taking this course thanks very much to everyone at Coursera, Google and DeepLearning.AI that contributed to this excellent content.

автор: Yanyun H

13 мая 2020 г.

Awesome course and amazing introduction to the time series predication using machine learning. Look forward to future more courses into more complex data scenarios. One of the best instructors I've had on Coursera. Thank you, Laurence.

автор: Priyank S

9 нояб. 2020 г.

This course provided an idea about the time series analysis with DNN's, LSTM's and CNN's which is a full package in learning neural networks. Instructors were very good and explained each and every code very thoroughly. Thank you !!

автор: Nitish T

3 окт. 2019 г.

The best introductory course on Sequence Models. I was intimidated by this topic before taking this course. Now, after training LSTMs and RNNs by hand, I am more comfortable. Thanks to Lawrence and Andrew for such a great course.

автор: Ourania S

16 янв. 2021 г.

It is really excited this course with so many nice different topics! Thanks a lot Laurence and Andrew for all your effort you have put on this course and moreover many thanks for transferring your knowledge in such an enjoy way!

автор: Pavan Y

30 июня 2020 г.

after taking Andrew's Deep Learning, this course is a logical step in two sense: 1. you can practice more 2. you do not need to write everything that are already output there through packages like TensorFlow. Excellent course!

автор: Zeeshan A

25 июня 2020 г.

The specialization covers brief introduction to the concepts of Computer Vision and Natural Language Processing. It introduces to TensorFlow and gives a hands-on practical experience over the tool through simple assignments.

автор: Gaurav P

22 июня 2020 г.

One of the best Specialization Courses In Coursera, Thank You so much Laurence for creating such a wonderful course and being such a awesome mentor and Thanks to Andrew too!! :) Looking forward to more such amazing courses.

автор: Daniel E

7 авг. 2019 г.

The specialization was packed with best practice fundamentals and I appreciated the explanations and lab work. My only concern is the lack of business focused problem sets that might bring us more up to speed with industry.

автор: ANMOL J

6 сент. 2020 г.

Amazing! and such a beautifully designed whole specialization that teaches you the practicality of tensorflow while holding a great understanding of indepth working!..Thank you! Lawrence and Andrew for such great courses !

автор: Luiz C

19 авг. 2019 г.

Eventually my favourite Course of the Specialization. Clear and learning content put in practice with focuses on the challenges of choosing DNN hyper-arameters and impact on their performance. Thank you for the good work

автор: Juan S B N

16 янв. 2021 г.

This course is great. The instructor took enough time to explain time series and how a neural network could identify the components of such time series. The introduction is great and the course material is quite useful.

автор: Dave P

2 февр. 2020 г.

A great course, wrapping up the specialization. The entire specialization has been very informative and inspirational. Thank you Laurence and thank you Andrew.

Like many others, would love to see what you produce next.

автор: Moustafa S

28 июня 2020 г.

this is by far the best course of this specialization, even tho i'm more into Computer Vision, but this course was by far so great and helpful to work on sequences and time varying data, really appreciate the effort.

автор: CLAUDIO C D R

2 мая 2020 г.

This specialization provides great insight into Tensorflow. It would have been nice to see algorithms mentioned in the Deep Learning specialization, such as the YOLO algorithm, implemented in the Tensorflow framework.

автор: Christopher G

2 авг. 2019 г.

I quickly learned a lot about how to represent time series and sequence data for prediction tasks, and how to combine different deep learning techniques together to get high-quality predictions. Another great course!