Envío a LUKA en todos los libros que quieras!  Ver más

menú

0
  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional
portada Applying Reinforcement Learning on Real-World Data with Practical Examples in Python (en Inglés)
Formato
Libro Físico
Editorial
Idioma
Inglés
N° páginas
92
Encuadernación
Tapa Blanda
Dimensiones
23.5 x 19.1 x 0.6 cm
Peso
0.20 kg.
ISBN13
9783031791666

Applying Reinforcement Learning on Real-World Data with Practical Examples in Python (en Inglés)

Philip Osborne (Autor) · Kajal Singh (Autor) · Matthew E. Taylor (Autor) · Springer · Tapa Blanda

Applying Reinforcement Learning on Real-World Data with Practical Examples in Python (en Inglés) - Osborne, Philip ; Singh, Kajal ; Taylor, Matthew E.

Libro Físico

$ 100.780

$ 167.970

Ahorras: $ 67.190

40% descuento
  • Estado: Nuevo
  • Quedan 100 unidades
Origen: Reino Unido (Costos de importación incluídos en el precio)
Se enviará desde nuestra bodega entre el Miércoles 10 de Julio y el Jueves 18 de Julio.
Lo recibirás en cualquier lugar de Chile entre 1 y 3 días hábiles luego del envío.

Reseña del libro "Applying Reinforcement Learning on Real-World Data with Practical Examples in Python (en Inglés)"

Reinforcement learning is a powerful tool in artificial intelligence in which virtual or physical agents learn to optimize their decision making to achieve long-term goals. In some cases, this machine learning approach can save programmers time, outperform existing controllers, reach super-human performance, and continually adapt to changing conditions. This book argues that these successes show reinforcement learning can be adopted successfully in many different situations, including robot control, stock trading, supply chain optimization, and plant control. However, reinforcement learning has traditionally been limited to applications in virtual environments or simulations in which the setup is already provided. Furthermore, experimentation may be completed for an almost limitless number of attempts risk-free. In many real-life tasks, applying reinforcement learning is not as simple as (1) data is not in the correct form for reinforcement learning, (2) data is scarce, and (3) automation has limitations in the real-world. Therefore, this book is written to help academics, domain specialists, and data enthusiast alike to understand the basic principles of applying reinforcement learning to real-world problems. This is achieved by focusing on the process of taking practical examples and modeling standard data into the correct form required to then apply basic agents. To further assist with readers gaining a deep and grounded understanding of the approaches, the book shows hand-calculated examples in full and then how this can be achieved in a more automated manner with code. For decision makers who are interested in reinforcement learning as a solution but are not technically proficient we include simple, non-technical examples in the introduction and case studies section. These provide context of what reinforcement learning offer but also the challenges and risks associated with applying it in practice. Specifically, the book illustrates the differences between reinforcement learning and other machine learning approaches as well as how well-known companies have found success using the approach to their problems.

Opiniones del libro

Ver más opiniones de clientes
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Preguntas frecuentes sobre el libro

Todos los libros de nuestro catálogo son Originales.
El libro está escrito en Inglés.
La encuadernación de esta edición es Tapa Blanda.

Preguntas y respuestas sobre el libro

¿Tienes una pregunta sobre el libro? Inicia sesión para poder agregar tu propia pregunta.

Opiniones sobre Buscalibre

Ver más opiniones de clientes