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Author Necmi Gürsakal , Sadullah Çelik , Esma Birişçi
Data is the indispensable fuel that drives the decision making of everything from governments, to major corporations, to sports teams. Its value is almost beyond measure. But what if that data is either unavailable or problematic to access? That’s where synthetic data comes in. This book will show y....
Release Date 2023/01 -
Modern Deep Learning for Tabular Data: Novel Approaches to Common Modeling Problems
Author Andre Ye , Zian Wang
Deep learning is one of the most powerful tools in the modern artificial intelligence landscape. While having been predominantly applied to highly specialized image, text, and signal datasets, this book synthesizes and presents novel deep learning approaches to a seemingly unlikely domain – tabular ....
Release Date 2022/12 -
Author Upendra Kumar Devisetty
Learn concepts, methodologies, and applications of deep learning for building predictive models from complex genomics data sets to overcome challenges in the life sciences and biotechnology industriesKey FeaturesApply deep learning algorithms to solve real-world problems in the field of genomicsExtr....
Release Date 2022/11 -
Deep Learning with R, Second Edition
Author Tomasz Kalinowski , Sigrid Keydana , J.J. Allaire , Francois Chollet
Deep learning from the ground up using R and the powerful Keras library! In Deep Learning with R, Second Edition you will learn: Deep learning from first principlesImage classification and image segmentationTime series forecastingText classification and machine translationText generation, neural....
Release Date 2022/10 -
Neural Search - From Prototype to Production with Jina
Author Bo Wang , Cristian Mitroi , Feng Wang , Shubham Saboo , Susana Guzmán
Implement neural search systems on the cloud by leveraging Jina design patternsKey FeaturesIdentify the different search techniques and discover applications of neural searchGain a solid understanding of vector representation and apply your knowledge in neural searchUnlock deeper levels of knowledge....
Release Date 2022/10 -
Deep Learning with TensorFlow and Keras - Third Edition
Author Amita Kapoor , Antonio Gulli , Sujit Pal , François Chollet
Build cutting edge machine and deep learning systems for the lab, production, and mobile devicesKey FeaturesUnderstand the fundamentals of deep learning and machine learning through clear explanations and extensive code samplesImplement graph neural networks, transformers using Hugging Face and Tens....
Release Date 2022/10 -
Author Xudong Ma , Vishakh Hegde , Lilit Yolyan
Visualize and build deep learning models with 3D data using PyTorch3D and other Python frameworks to conquer real-world application challenges with easeKey FeaturesUnderstand 3D data processing with rendering, PyTorch optimization, and heterogeneous batchingImplement differentiable rendering concept....
Release Date 2022/10 -
Production-Ready Applied Deep Learning
Author Tomasz Palczewski , Jaejun Lee , Lenin Mookiah
Supercharge your skills for developing powerful deep learning models and distributing them at scale efficiently using cloud servicesKey FeaturesUnderstand how to execute a deep learning project effectively using various tools availableLearn how to develop PyTorch and TensorFlow models at scale using....
Release Date 2022/08 -
Author Konrad Banachewicz , Luca Massaron , Anthony Goldbloom
Get a step ahead of your competitors with insights from over 30 Kaggle Masters and Grandmasters. Discover tips, tricks, and best practices for competing effectively on Kaggle and becoming a better data scientist. Purchase of the print or Kindle book includes a free eBook in the PDF format.Key Fea....
Release Date 2022/04 -
Fundamentals and Methods of Machine and Deep Learning
Author Pradeep Singh
FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNINGThe book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications.Over the past two decades, the field of machine ....
Release Date 2022/03 -
Intelligent Systems for Rehabilitation Engineering
Author Roshani Raut , Pranav Pathak , Sandeep Kautish , Pradeep N.
INTELLIGENT SYSTEMS FOR REHABILITATION ENGINEERINGEncapsulates different case studies where technology can be used as assistive technology for the physically challenged, visually and hearing impaired. Rehabilitation engineering includes the development of technological solutions and devices to assis....
Release Date 2022/02 -
Author Andre Ye
Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and deep-learning case studies, this book reveals how to acquire the tools you need to design and implement like a deep-learning architect. It covers tools deep learnin....
Release Date 2021/11 -
Fundamentals of Deep Learning, 2nd Edition
We're in the midst of an AI research explosion. Deep learning has unlocked superhuman perception that has powered our push toward self-driving vehicles, the ability to defeat human experts at a variety of difficult games including Go and Starcraft, and even generate essays with shockingly coherent .... -
Deep Learning for Chest Radiographs
Author Yashvi Chandola , Jitendra Virmani , H.S Bhadauria , Papendra Kumar
Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectio....
Release Date 2021/07 -
Automated Machine Learning with AutoKeras
Create better and easy-to-use deep learning models with AutoKerasKey FeaturesDesign and implement your own custom machine learning models using the features of AutoKerasLearn how to use AutoKeras for techniques such as classification, regression, and sentiment analysisGet familiar with advanced conc.... -
Distributed Data Systems with Azure Databricks
Quickly build and deploy massive data pipelines and improve productivity using Azure DatabricksKey FeaturesGet to grips with the distributed training and deployment of machine learning and deep learning modelsLearn how ETLs are integrated with Azure Data Factory and Delta LakeExplore deep learning a.... -
Deep Learning with Python: Learn Best Practices of Deep Learning Models with PyTorch
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-.... -
Deep Learning with Structured Data
Deep Learning with Structured Data teaches you powerful data analysis techniques for tabular data and relational databases. Get started using a dataset based on the Toronto transit system. As you work through the book, you’ll learn how easy it is to set up tabular data for deep learning, while solvi.... -
Deep Learning on Windows: Building Deep Learning Computer Vision Systems on Microsoft Windows
Build deep learning and computer vision systems using Python, TensorFlow, Keras, OpenCV, and more, right within the familiar environment of Microsoft Windows. The book starts with an introduction to tools for deep learning and computer vision tasks followed by instructions to install, configure.... -
Trends in Deep Learning Methodologies
Author Vincenzo Piuri , Sandeep Raj , Angelo Genovese , Rajshree Srivastava
Trends in Deep Learning Methodologies: Algorithms, Applications, and Systems covers deep learning approaches such as neural networks, deep belief networks, recurrent neural networks, convolutional neural networks, deep auto-encoder, and deep generative networks, which have emerged as powerful comput....
Release Date 2020/11 -
Applied Neural Networks with TensorFlow 2: API Oriented Deep Learning with Python
Author Orhan Gazi Yalçın
Implement deep learning applications using TensorFlow while learning the “why” through in-depth conceptual explanations. You’ll start by learning what deep learning offers over other machine learning models. Then familiarize yourself with several technologies ....
Release Date 2020/11 -
Deep Learning for Vision Systems
Author Mohamed Elgendy
How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand h....
Release Date 2020/11 -
Codeless Deep Learning with KNIME
Discover how to integrate KNIME Analytics Platform with deep learning libraries to implement artificial intelligence solutionsKey FeaturesBecome well-versed with KNIME Analytics Platform to perform codeless deep learningDesign and build deep learning workflows quickly and more easily using the KNIME.... -
Author Dr. Pablo Rivas , Laura Montoya
Implementing supervised, unsupervised, and generative deep learning (DL) models using Keras and Dopamine over TensorFlow.Key FeaturesUnderstand the fundamental machine learning concepts useful in deep learningLearn the underlying mathematical concepts as you implement dee....
Release Date 2020/09 -
Deep Learning for Coders with fastai and PyTorch
Author Jeremy Howard , Sylvain Gugger
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and ....
Release Date 2020/07 -
The Deep Learning with Keras Workshop
Author Matthew Moocarme , Mahla Abdolahnejad , Ritesh Bhagwat
Discover how to leverage Keras, the powerful and easy-to-use open source Python library for developing and evaluating deep learning modelsKey FeaturesGet to grips with various model evaluation metrics, including sensitivity, specificity, and AUC scores Explore advanced c....
Release Date 2020/07