Better Deep Learning
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Better Deep Learning
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Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2018-12-13
Better Deep Learning written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-13 with Computers categories.
Deep learning neural networks have become easy to define and fit, but are still hard to configure. Discover exactly how to improve the performance of deep learning neural network models on your predictive modeling projects. With clear explanations, standard Python libraries, and step-by-step tutorial lessons, you’ll discover how to better train your models, reduce overfitting, and make more accurate predictions.
Deep Learning For Dummies
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Author : John Paul Mueller
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-15
Deep Learning For Dummies written by John Paul Mueller and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-15 with Computers categories.
Take a deep dive into deep learning Deep learning provides the means for discerning patterns in the data that drive online business and social media outlets. Deep Learning for Dummies gives you the information you need to take the mystery out of the topic—and all of the underlying technologies associated with it. In no time, you’ll make sense of those increasingly confusing algorithms, and find a simple and safe environment to experiment with deep learning. The book develops a sense of precisely what deep learning can do at a high level and then provides examples of the major deep learning application types. Includes sample code Provides real-world examples within the approachable text Offers hands-on activities to make learning easier Shows you how to use Deep Learning more effectively with the right tools This book is perfect for those who want to better understand the basis of the underlying technologies that we use each and every day.
Deep Learning Essentials
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Author : Anurag Bhardwaj
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-01-30
Deep Learning Essentials written by Anurag Bhardwaj and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-01-30 with Computers categories.
Get to grips with the essentials of deep learning by leveraging the power of Python Key Features Your one-stop solution to get started with the essentials of deep learning and neural network modeling Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner Book Description Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more. This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications. What you will learn Get to grips with the core concepts of deep learning and neural networks Set up deep learning library such as TensorFlow Fine-tune your deep learning models for NLP and Computer Vision applications Unify different information sources, such as images, text, and speech through deep learning Optimize and fine-tune your deep learning models for better performance Train a deep reinforcement learning model that plays a game better than humans Learn how to make your models get the best out of your GPU or CPU Who this book is for Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python.
Neural Networks And Deep Learning
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Author : Charu C. Aggarwal
language : en
Publisher: Springer
Release Date : 2018-08-25
Neural Networks And Deep Learning written by Charu C. Aggarwal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-25 with Computers categories.
This book covers both classical and modern models in deep learning. The primary focus is on the theory and algorithms of deep learning. The theory and algorithms of neural networks are particularly important for understanding important concepts, so that one can understand the important design concepts of neural architectures in different applications. Why do neural networks work? When do they work better than off-the-shelf machine-learning models? When is depth useful? Why is training neural networks so hard? What are the pitfalls? The book is also rich in discussing different applications in order to give the practitioner a flavor of how neural architectures are designed for different types of problems. Applications associated with many different areas like recommender systems, machine translation, image captioning, image classification, reinforcement-learning based gaming, and text analytics are covered. The chapters of this book span three categories: The basics of neural networks: Many traditional machine learning models can be understood as special cases of neural networks. An emphasis is placed in the first two chapters on understanding the relationship between traditional machine learning and neural networks. Support vector machines, linear/logistic regression, singular value decomposition, matrix factorization, and recommender systems are shown to be special cases of neural networks. These methods are studied together with recent feature engineering methods like word2vec. Fundamentals of neural networks: A detailed discussion of training and regularization is provided in Chapters 3 and 4. Chapters 5 and 6 present radial-basis function (RBF) networks and restricted Boltzmann machines. Advanced topics in neural networks: Chapters 7 and 8 discuss recurrent neural networks and convolutional neural networks. Several advanced topics like deep reinforcement learning, neural Turing machines, Kohonen self-organizing maps, and generative adversarial networks are introduced in Chapters 9 and 10. The book is written for graduate students, researchers, and practitioners. Numerous exercises are available along with a solution manual to aid in classroom teaching. Where possible, an application-centric view is highlighted in order to provide an understanding of the practical uses of each class of techniques.
Advances On Machine And Deep Learning Techniques In Modern Strategies
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Author : Mr.Chitra Sabapathy Ranganathan
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-04-02
Advances On Machine And Deep Learning Techniques In Modern Strategies written by Mr.Chitra Sabapathy Ranganathan and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-02 with Computers categories.
Mr.Chitra Sabapathy Ranganathan, Associate Vice President, Mphasis Corporation, Arizona, USA
Deep Learning
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Author : Mr. Rohit Manglik
language : en
Publisher: EduGorilla Publication
Release Date : 2024-07-07
Deep Learning written by Mr. Rohit Manglik and has been published by EduGorilla Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-07 with Computers categories.
EduGorilla Publication is a trusted name in the education sector, committed to empowering learners with high-quality study materials and resources. Specializing in competitive exams and academic support, EduGorilla provides comprehensive and well-structured content tailored to meet the needs of students across various streams and levels.
Deep Learning With Pytorch
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Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2023-03-21
Deep Learning With Pytorch written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Computers categories.
Deep learning is currently the most interesting and powerful machine learning technique. PyTorch is one of the dominant libraries for deep learning in the Python ecosystem and is widely used in research. With PyTorch, you can easily tap into the power of deep learning with just a few lines of code. Many deep learning models are created in PyTorch. Therefore, knowing PyTorch opens the door for you to leverage the power of deep learning. This Ebook is written in the friendly Machine Learning Mastery style that you’re used to, learn exactly how to get started and apply deep learning to your own machine learning projects.
Deep Learning In Natural Language Processing
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Author : Li Deng
language : en
Publisher: Springer
Release Date : 2018-05-23
Deep Learning In Natural Language Processing written by Li Deng and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-23 with Computers categories.
In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.
Intelligent Systems Bridging Machine Learning Deep Learning And Natural Language Processing
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Author : Dr.Sudhakar.K
language : en
Publisher: Leilani Katie Publication
Release Date : 2024-11-26
Intelligent Systems Bridging Machine Learning Deep Learning And Natural Language Processing written by Dr.Sudhakar.K and has been published by Leilani Katie Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-26 with Computers categories.
Dr.Sudhakar.K, Associate Professor & Head, Department of Artificial Intelligence & Data Science, NITTE Meenakshi Institute of Technology, Bangalore, Karnataka, India. Dr.R.Vadivel, Associate Professor, Department of Artificial Intelligence & Data Science, NITTE Meenakshi Institute of Technology, Bangalore, Karnataka, India. Ms.Sarumathi.S, Assistant Professor, Department of Computer Science and Engineering, HKBK College of Engineering, Bangalore, Karnataka, India. Dr.Manjunatha.S, Professor, Department of Computer Science and Engineering, BNM Institute of Technology, Bangalore, Karnataka, India.
Deep Learning For Beginners
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Author : Steven Cooper
language : en
Publisher: Roland Bind
Release Date : 2018-11-06
Deep Learning For Beginners written by Steven Cooper and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-06 with Computers categories.
☆★The Best Deep Learning Book for Beginners★☆ If you are looking for a complete beginners guide to learn deep learning with examples, in just a few hours, then you need to continue reading. This book delves into the basics of deep learning for those who are enthusiasts concerning all things machine learning and artificial intelligence. For those who have seen movies which show computer systems taking over the world like, Terminator, or benevolent systems that watch over the population, i.e. Person of Interest, this should be right up your alley. This book will give you the basics of what deep learning entails. That means frameworks used by coders and significant components and tools used in deep learning, that enable facial recognition, speech recognition, and virtual assistance. Yes, deep learning provides the tools through which systems like Siri became possible. ★★ Grab your copy today and learn ★★ ♦ Deep learning utilizes frameworks which allow people to develop tools which are able to offer better abstraction, along with simplification of hard programming issues. TensorFlow is the most popular tool and is used by corporate giants such as Airbus, Twitter, and even Google. ♦ The book illustrates TensorFlow and Caffe2 as the prime frameworks that are used for development by Google and Facebook. Facebook illustrates Caffe2 as one of the lightweight and modular deep learning frameworks, though TensorFlow is the most popular one, considering it has a lot of popularity, and thus, a big forum, which allows for assistance on main problems. ♦ The book considers several components and tools of deep learning such as the neural networks; CNNs, RNNs, GANs, and auto-encoders. These algorithms create the building blocks which propel deep learning and advance it. ♦ The book also considers several applications, including chatbots and virtual assistants, which have become the main focus for deep learning into the future, as they represent the next frontier in information gathering and connectivity. The Internet of Things is also represented here, as deep learning allows for the integration of various systems via an artificial intelligence system, which is already being used for the home and car functions. ♦ And much more... The use of data science adds a lot of value to businesses, and we will continue to see the need for data scientists grow. This book is probably one of the best books for beginners. It's a step-by-step guide for any person who wants to start learning deep learning and artificial intelligence from scratch. When data science can reduce spending costs by billions of dollars in the healthcare industry, why wait to jump in? If you want to get started on deep learning and the concepts that run artificial technologies, don't wait any longer. Scroll up and click the buy now button to get this book today!