These signals of five different classes have been used as the feature vector in the training of machine learning algorithms with 10 statistical parameters (8 normalized, 2 real signals). In this study, a new hybrid model has been developed to classify EEG and ECG signals. Due to the successful application methods of EEG and ECG signals in classification problems, various fields of artificial intelligence applications are frequently used by experts. In order to use this information, experts in the field of signal processing must evaluate these signals. These signs contain a large amount of information about the functioning of the brain and heart functions. EEG signals examine the neural activity of the brain, while ECG examines the work of the heart muscle and neural conduction system. Electroencephalogram (EEG) and electrocardiogram (ECG) are frequently used in the diagnosis of diseases and research in this field. Time series are used in many fields to understand the behavior of systems, to make predictions, to create solutions to problems, etc. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization.A time series is a sequence of numerical data points in equal time intervals and/or successive order. 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. The Machine Learning course and Deep Learning Specialization from Andrew Ng teach the most important and foundational principles of Machine Learning and Deep Learning. Finally, you’ll apply everything you’ve learned throughout the Specialization to build a sunspot prediction model using real-world data! You’ll also explore how RNNs and 1D ConvNets can be used for prediction.

You’ll first implement best practices to prepare time series data. In this fourth course, you will learn how to build time series models in TensorFlow.

This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. 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.

Time series machine learning models