Detalhes do Livro
Formato
Brochura
Páginas
698
Idioma
Inglês
Publicado
Oct 6, 2022
Editora
Packt Publishing
Edição
3rd ed.
ISBN-10
1803232919
ISBN-13
9781803232911
Descrição
This insightful guide delves into the vibrant world of deep learning, providing readers with a comprehensive understanding of TensorFlow and Keras. With clear explanations and practical examples, the authors Amita Kapoor, Antonio Gulli, and Sujit Pal bring complex concepts to life, making them accessible to both new and seasoned practitioners.
The book offers a balanced mix of theory and hands-on learning, covering a variety of essential topics, including supervised and unsupervised learning, as well as deep and reinforcement learning models. Readers will appreciate the structured approach that breaks down intricate ideas into manageable pieces, allowing them to grasp advanced techniques effortlessly.
As they progress, readers are encouraged to build and deploy their own models, gaining invaluable experience along the way. The third edition ensures that the content remains up-to-date, reflecting the latest advancements in the field.
Overall, this resource stands out as an essential companion for anyone looking to enhance their skills in deep learning and effectively harness the power of TensorFlow and Keras.
The book offers a balanced mix of theory and hands-on learning, covering a variety of essential topics, including supervised and unsupervised learning, as well as deep and reinforcement learning models. Readers will appreciate the structured approach that breaks down intricate ideas into manageable pieces, allowing them to grasp advanced techniques effortlessly.
As they progress, readers are encouraged to build and deploy their own models, gaining invaluable experience along the way. The third edition ensures that the content remains up-to-date, reflecting the latest advancements in the field.
Overall, this resource stands out as an essential companion for anyone looking to enhance their skills in deep learning and effectively harness the power of TensorFlow and Keras.
Gêneros
Ciência e Tecnologia