using neural networks time series de continental academy press (4 resultados)

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Using Neural Networks for Time Series Analysis is a cutting-edge guide that explores the application of neural networks in time series analysis. By leveraging the power of machine learning, this book demonstrates how neural networks can be employed to forecast and predict complex time series data. The author provides a detailed explanation of the underlying theory and mathematics, as well as practical examples and case studies to illustrate the effectiveness of neural networks in time series analysis. From data preprocessing to model evaluation, this book covers the essential steps required to build and deploy neural network models for time series forecasting. By mastering the techniques outlined in this book, readers can develop a deeper understanding of neural networks and their applications in time series analysis. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Recurrent neural networks (RNNs) are a type of deep learning algorithm that's revolutionizing the field of time series prediction. Using Recurrent Neural Networks for Time Series Prediction provides a comprehensive guide to understanding the principles and applications of RNNs, from forecasting stock prices to predicting weather patterns. By mastering the art of RNNs, you'll learn how to develop sophisticated time series prediction systems that can analyze and understand complex data with unprecedented accuracy. This book will walk you through the process of designing, training, and deploying RNNs for a wide range of applications, from finance to healthcare. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Time series forecasting is a critical task in various industries, including finance, weather prediction, and supply chain management. In 'Using Neural Networks for Time Series Forecasting,' we examine the application of neural networks in predicting future values based on historical data. By exploring different architectures, including recurrent neural networks and long short-term memory (LSTM) networks, we can develop robust forecasting models that capture complex patterns and trends in time series data. This in-depth guide provides a comprehensive overview of the challenges and opportunities in time series forecasting using neural networks. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.

Softcover. Condición: New. Estado de la sobrecubierta: no dj. First. Time series forecasting is a critical component of many industries, from finance to healthcare, yet the complexity of these data sets can be overwhelming. 'Using Recurrent Neural Networks for Time Series Forecasting' offers a cutting-edge exploration of recurrent neural networks (RNNs), a powerful technique for modeling and predicting time series data. By examining the applications and limitations of RNNs in time series forecasting, this book provides a comprehensive overview of the latest developments in the field, including the use of long short-term memory (LSTM) networks and gated recurrent units (GRUs). With its focus on practical implementation and real-world examples, readers will gain a deeper understanding of how to harness the power of RNNs to build more accurate, efficient, and effective time series forecasting systems. Publication Year: 2025. SHIPPING TERMS - Depending on your location we may ship your book from the following locations: France, United Kingdom, India, Australia, Canada or the USA. This item is printed on demand.