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.
Этот курс входит в специализацию ''Профессиональная сертификация 'TensorFlow-разработчик от deeplearning.ai''
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Об этом курсе
You should take the first 3 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.
Чему вы научитесь
Solve time series and forecasting problems in TensorFlow
Prepare data for time series learning using best practices
Explore how RNNs and ConvNets can be used for predictions
Build a sunspot prediction model using real-world data
Приобретаемые навыки
- Forecasting
- Machine Learning
- Tensorflow
- Time Series
- prediction
You should take the first 3 courses of the TensorFlow Specialization and be comfortable coding in Python and understanding high school-level math.
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deeplearning.ai
DeepLearning.AI is an education technology company that develops a global community of AI talent.
Программа курса: что вы изучите
Sequences and Prediction
Hi Learners and welcome to this course on sequences and prediction! In this course we'll take a look at some of the unique considerations involved when handling sequential time series data -- where values change over time, like the temperature on a particular day, or the number of visitors to your web site. We'll discuss various methodologies for predicting future values in these time series, building on what you've learned in previous courses!
Deep Neural Networks for Time Series
Having explored time series and some of the common attributes of time series such as trend and seasonality, and then having used statistical methods for projection, let's now begin to teach neural networks to recognize and predict on time series!
Recurrent Neural Networks for Time Series
Recurrent Neural networks and Long Short Term Memory networks are really useful to classify and predict on sequential data. This week we'll explore using them with time series...
Real-world time series data
On top of DNNs and RNNs, let's also add convolutions, and then put it all together using a real-world data series -- one which measures sunspot activity over hundreds of years, and see if we can predict using it.
Рецензии
- 5 stars76,59 %
- 4 stars16,80 %
- 3 stars4,08 %
- 2 stars1,22 %
- 1 star1,28 %
Лучшие отзывы о курсе SEQUENCES, TIME SERIES AND PREDICTION
The course is easy to follow and focuses on how to implement theoretical concepts using tensor flow. The way Lawrence approaches the sessions makes it really interesting and fun to learn!
Laurence Moroney is the best. Before taking up the course, i didnt know anything about the AI or ML or Tensorflow. The concepts were explained in such a manner that anyone can learn Tensorflow.
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.
The course is fantastic. It was a bit short and with some hyperparameters tuning focus, it could have been great. Also, it seems that it is biased to show that LSTM is always superior to RNN networks.
Профессиональная сертификация 'TensorFlow-разработчик от deeplearning.ai': общие сведения
TensorFlow is one of the most in-demand and popular open-source deep learning frameworks available today. The DeepLearning.AI TensorFlow Developer Professional Certificate program teaches you applied machine learning skills with TensorFlow so you can build and train powerful models.

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