Deep Learning in Time Series Analysis
Deep learning is an important element of artificial intelligence especially in applications such as image classification in which various architectures of neural network e. g. convolutional neural networks have yielded reliable results. This book introduces deep learning for time series analysis particularly for cyclic time series. It elaborates on the methods employed for time series analysis at the deep level of their architectures. Cyclic time series usually have special traits that can be employed for better classification performance. These are addressed in the book. Processing cyclic time series is also covered herein. An important factor in classifying stochastic time series is the structural risk associated with the architecture of classification methods. The book addresses and formulates structural risk and the learning capacity defined for a classification method. These formulations and the mathematical derivations will help the researchers in understanding the methods and even express their methodologies in an objective mathematical way. The book has been designed as a self-learning textbook for the readers with different backgrounds and understanding levels of machine learning including students engineers researchers and scientists of this domain. The numerous informative illustrations presented by the book will lead the readers to a deep level of understanding about the deep learning methods for time series analysis. | Deep Learning in Time Series Analysis
Price now:
£120.00
Price History:
Details:Deep Learning in Time Series Analysis
Deep learning is an important element of artificial intelligence especially in applications such as image classification in which various architectures of neural network e. g. convolutional neural networks have yielded reliable results. This book introduces deep learning for time series analysis particularly for cyclic time series. It elaborates on the methods employed for time series analysis at the deep level of their architectures. Cyclic time series usually have special traits that can be employed for better classification performance. These are addressed in the book. Processing cyclic time series is also covered herein. An important factor in classifying stochastic time series is the structural risk associated with the architecture of classification methods. The book addresses and formulates structural risk and the learning capacity defined for a classification method. These formulations and the mathematical derivations will help the researchers in understanding the methods and even express their methodologies in an objective mathematical way. The book has been designed as a self-learning textbook for the readers with different backgrounds and understanding levels of machine learning including students engineers researchers and scientists of this domain. The numerous informative illustrations presented by the book will lead the readers to a deep level of understanding about the deep learning methods for time series analysis. | Deep Learning in Time Series Analysis
Price now:
£120.00
Routledge
4.35% (+ £5.00)
New
£120.00
Product Description
Deep learning is an important element of artificial intelligence especially in applications such as image classification in which various architectures of neural network e. g. convolutional neural networks have yielded reliable results. This book introduces deep learning for time series analysis particularly for cyclic time series. It elaborates on the methods employed for time series analysis at the deep level of their architectures. Cyclic time series usually have special traits that can be employed for better classification performance. These are addressed in the book. Processing cyclic time series is also covered herein. An important factor in classifying stochastic time series is the structural risk associated with the architecture of classification methods. The book addresses and formulates structural risk and the learning capacity defined for a classification method. These formulations and the mathematical derivations will help the researchers in understanding the methods and even express their methodologies in an objective mathematical way. The book has been designed as a self-learning textbook for the readers with different backgrounds and understanding levels of machine learning including students engineers researchers and scientists of this domain. The numerous informative illustrations presented by the book will lead the readers to a deep level of understanding about the deep learning methods for time series analysis. | Deep Learning in Time Series Analysis
Product Specifications
General | |
|---|---|
Material | lead |
Brand | CRC Press |
Related Products
£35.99
Amazon
£43.40
Amazon
£43.40
Amazon
£44.00
Amazon
£18.25
Amazon
Delivery, Returns & Refunds
Delivery
Sellers offer a range of delivery options, so you can choose the one that’s most convenient for you. Many sellers offer free delivery. You can always find the postage cost and estimated delivery date in a seller’s listing. You'll then be able to see a full list of delivery options during checkout. These can include: Express delivery, Standard delivery, Economy delivery, Click & Collect, Free local collection from seller.
Returns
Your options for returning an item vary depending on what you want to return, why you want to return it, and the seller's return policy. If the item is damaged or doesn't match the listing description, you can return it even if the seller's returns policy says they don't accept returns. If you've changed your mind and no longer want an item, you can still request a return, but the seller doesn't have to accept it. If the buyer changes their mind about a purchase and wants to return an item, they may need to pay return postage costs, depending on the seller's return policy. Sellers can provide a return postage address and additional return postage information for the buyer. Sellers pay for return postage if there's a problem with the item. For example, if the item doesn't match the listing description, is damaged or defective or is counterfeit. By law, customers in the European Union also have the right to cancel the purchase of an item within 14 days beginning from the day you receive, or a third party indicated by you (other than the carrier) receives, the last good ordered by you (if delivered separately). This applies to all products except for digital items (e.g. Digital Music) that are provided immediately to you with your acknowledgement, and other items such as video, DVD, audio, video games, Sex and Sensuality products and software products where the item has been unsealed.
Refunds
Sellers have to offer a refund for certain items only if they are faulty, such as: Personalised items and custom-made items, Perishable items, Newspapers and magazines, Unwrapped CDs DVDs and computer software. If you used your PayPal balance or bank account to fund the original payment, the refunded money will go back to your PayPal account balance. If you used a credit or debit card to fund the original payment, the refunded money will go back to your card. The seller will effect the refund within three working days but it may take up to 30 days for Paypal to process the transfer. For payments funded partially by a card and partially by your balance/bank, the money taken from your card will go back to your card and the remainder will return to your PayPal balance.