Deep Learning And Its Applications Using Python
Download Deep Learning And Its Applications Using Python PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Deep Learning And Its Applications Using Python book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Deep Learning and its Applications using Python
Author: Niha Kamal Basha
language: en
Publisher: John Wiley & Sons
Release Date: 2023-10-31
This book thoroughly explains deep learning models and how to use Python programming to implement them in applications such as NLP, face detection, face recognition, face analysis, and virtual assistance (chatbot, machine translation, etc.). It provides hands-on guidance in using Python for implementing deep learning application models. It also identifies future research directions for deep learning.
Deep Learning and its Applications using Python
Author: Niha Kamal Basha
language: en
Publisher: John Wiley & Sons
Release Date: 2023-09-27
DEEP LEARNING AND ITS APPLICATIONS USING PYTHON This practical book gives a detailed description of deep learning models and their implementation using Python programming relating to computer vision, natural language processing, and other applications. This book thoroughly explains deep learning models and how to use Python programming to implement them in applications such as NLP, face detection, face recognition, face analysis, and virtual assistance (chatbot, machine translation, etc.). It provides hands-on guidance in using Python for implementing deep learning application models. It also identifies future research directions for deep learning. Readers/users will discover A precise description of deep learning history, fundamental concepts, and background information relating to deep learning; A detailed introduction to several concepts including tensorflow and keras, starting from the fundamentals to the application-based concept implementation using Python; Explanations of multilayer perceptron, convolutional neural network, recurrent neural network, and long short-term memory in terms of applications like chatbot, face detection and recognition; Advanced deep learning concepts along with their future research advancements; Assist in building the reader’s understanding through intuitive explanations and practical examples by exploring challenging concepts in the related applications of computer vision, natural language processing, and other models. Audience The book is ideal for computer science researchers, industry professionals, as well as postgraduate and undergraduate students who want to learn how to program deep learning models using Python.
Hands-On Python Deep Learning for the Web
Author: Anubhav Singh
language: en
Publisher: Packt Publishing Ltd
Release Date: 2020-05-15
Use the power of deep learning with Python to build and deploy intelligent web applications Key FeaturesCreate next-generation intelligent web applications using Python libraries such as Flask and DjangoImplement deep learning algorithms and techniques for performing smart web automationIntegrate neural network architectures to create powerful full-stack web applicationsBook Description When used effectively, deep learning techniques can help you develop intelligent web apps. In this book, you'll cover the latest tools and technological practices that are being used to implement deep learning in web development using Python. Starting with the fundamentals of machine learning, you'll focus on DL and the basics of neural networks, including common variants such as convolutional neural networks (CNNs). You'll learn how to integrate them into websites with the frontends of different standard web tech stacks. The book then helps you gain practical experience of developing a deep learning-enabled web app using Python libraries such as Django and Flask by creating RESTful APIs for custom models. Later, you'll explore how to set up a cloud environment for deep learning-based web deployments on Google Cloud and Amazon Web Services (AWS). Next, you'll learn how to use Microsoft's intelligent Emotion API, which can detect a person's emotions through a picture of their face. You'll also get to grips with deploying real-world websites, in addition to learning how to secure websites using reCAPTCHA and Cloudflare. Finally, you'll use NLP to integrate a voice UX through Dialogflow on your web pages. By the end of this book, you'll have learned how to deploy intelligent web apps and websites with the help of effective tools and practices. What you will learnExplore deep learning models and implement them in your browserDesign a smart web-based client using Django and FlaskWork with different Python-based APIs for performing deep learning tasksImplement popular neural network models with TensorFlow.jsDesign and build deep web services on the cloud using deep learningGet familiar with the standard workflow of taking deep learning models into productionWho this book is for This deep learning book is for data scientists, machine learning practitioners, and deep learning engineers who are looking to perform deep learning techniques and methodologies on the web. You will also find this book useful if you’re a web developer who wants to implement smart techniques in the browser to make it more interactive. Working knowledge of the Python programming language and basic machine learning techniques will be beneficial.