Applied Deep Learning with Python
Idioma: inglés
Editorial: Packt Publishing Limited, GB, 2018
- Tapa blanda
- Nuevo
Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
Vendedor de AbeBooks desde 11 de junio de 2025
Condición: Nuevo
EUR 60,16
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Añadir al carritoDescripción del artículo del vendedor
A hands-on guide to deep learning that's filled with intuitive explanations and engaging practical examplesKey FeaturesDesigned to iteratively develop the skills of Python users who don't have a data science backgroundCovers the key foundational concepts you'll need to know when building deep learning systemsComplete with step-by-step exercises and activities to help you build the skills you need for the real worldBook DescriptionTaking an approach that uses the latest developments in the Python ecosystem, you'll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before you train your first predictive model. You'll then explore a variety of approaches to classification such as support vector networks, random decision forests and k-nearest neighbors to build on your knowledge before moving on to advanced topics.After covering classification, you'll go on to discover ethical web scraping and interactive visualizations, which will help you professionally gather and present your analysis. Next, you'll start building your keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data. You'll then be guided through a trained neural network, which will help you explore common deep learning network architectures (convolutional, recurrent, and generative adversarial networks) and deep reinforcement learning. Later, you'll delve into model optimization and evaluation. You'll do all this while working on a production-ready web application that combines TensorFlow and Keras to produce meaningful user-friendly results.By the end of this book, you'll be equipped with the skills you need to tackle and develop your own real-world deep learning projects confidently and effectively.What you will learnDiscover how you can assemble and clean your very own datasetsDevelop a customized machine learning classification strategyBuild, train and enhance your own models to solve unique problemsWork with production-ready frameworks such as TensorFlow and KerasUnderstand how neural networks operate in clear and simple termsDeploy your predictions to the webWho this book is forIf you're a Python programmer stepping into the world of data science, this is the ideal way to get started. …
N° de ref. del artículo LU-9781789804744
- Título
- Applied Deep Learning with Python
- Autor
- Luis Capelo, Alex Galea
- Editorial
- Packt Publishing Limited, GB
- Año de publicación
- 2018
- Estado
- New
- Encuadernación
- Paperback
- Idioma
- inglés
- ISBN 10
- 1789804744
- ISBN 13
- 9781789804744
A hands-on guide to deep learning that's filled with intuitive explanations and engaging practical examples
Key Features
- Designed to iteratively develop the skills of Python users who don't have a data science background
- Covers the key foundational concepts you'll need to know when building deep learning systems
- Full of step-by-step exercises and activities to help build the skills that you need for the real-world
Book Description
Taking an approach that uses the latest developments in the Python ecosystem, you'll first be guided through the Jupyter ecosystem, key visualization libraries and powerful data sanitization techniques before we train our first predictive model. We'll explore a variety of approaches to classification like support vector networks, random decision forests and k-nearest neighbours to build out your understanding before we move into more complex territory. It's okay if these terms seem overwhelming; we'll show you how to put them to work.
We'll build upon our classification coverage by taking a quick look at ethical web scraping and interactive visualizations to help you professionally gather and present your analysis. It's after this that we start building out our keystone deep learning application, one that aims to predict the future price of Bitcoin based on historical public data.
By guiding you through a trained neural network, we'll explore common deep learning network architectures (convolutional, recurrent, generative adversarial) and branch out into deep reinforcement learning before we dive into model optimization and evaluation. We'll do all of this whilst working on a production-ready web application that combines Tensorflow and Keras to produce a meaningful user-friendly result, leaving you with all the skills you need to tackle and develop your own real-world deep learning projects confidently and effectively.
What you will learn
- Discover how you can assemble and clean your very own datasets
- Develop a tailored machine learning classification strategy
- Build, train and enhance your own models to solve unique problems
- Work with production-ready frameworks like Tensorflow and Keras
- Explain how neural networks operate in clear and simple terms
- Understand how to deploy your predictions to the web
Who this book is for
If you're a Python programmer stepping into the world of data science, this is the ideal way to get started.
Table of Contents
- Jupyter Fundamentals
- Data Cleaning and Advanced Machine Learning
- Web Scraping and Interactive Visualizations
- Introduction to Neural Networks and Deep Learning
- Model Architecture
- Model Evaluation
- Productization
“Sinopsis” puede pertenecer a otra edición de este título.
Acerca del autor
Luis Capelo is a Harvard-trained analyst and a programmer, who specializes in designing and developing data science products. He is based in New York City, America. Luis is the head of the Data Products team at Forbes, where they investigate new techniques for optimizing article performance and create clever bots that help them distribute their content. He worked for the United Nations as part of the Humanitarian Data Exchange team (founders of the Center for Humanitarian Data). Later on, he led a team of scientists at the Flowminder Foundation, developing models for assisting the humanitarian community. Luis is a native of Havana, Cuba, and the founder and owner of a small consultancy firm dedicated to supporting the nascent Cuban private sector.
“Acerca de” puede pertenecer a otra edición de este título.
Rarewaves.com UK
London, Reino Unido
Vendedor de AbeBooks desde 11 de junio de 2025
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