Deep Learning In Science
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Deep Learning In Science
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Author : Pierre Baldi
language : en
Publisher: Cambridge University Press
Release Date : 2021-07
Deep Learning In Science written by Pierre Baldi and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07 with Computers categories.
Rigorous treatment of the theory of deep learning from first principles, with applications to beautiful problems in the natural sciences.
Deep Learning For The Life Sciences
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Author : Bharath Ramsundar
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-04-10
Deep Learning For The Life Sciences written by Bharath Ramsundar and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-10 with Science categories.
Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working
The Science Of Deep Learning
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Author : Iddo Drori
language : en
Publisher: Cambridge University Press
Release Date : 2022-08-18
The Science Of Deep Learning written by Iddo Drori and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-18 with Computers categories.
The Science of Deep Learning emerged from courses taught by the author that have provided thousands of students with training and experience for their academic studies, and prepared them for careers in deep learning, machine learning, and artificial intelligence in top companies in industry and academia. The book begins by covering the foundations of deep learning, followed by key deep learning architectures. Subsequent parts on generative models and reinforcement learning may be used as part of a deep learning course or as part of a course on each topic. The book includes state-of-the-art topics such as Transformers, graph neural networks, variational autoencoders, and deep reinforcement learning, with a broad range of applications. The appendices provide equations for computing gradients in backpropagation and optimization, and best practices in scientific writing and reviewing. The text presents an up-to-date guide to the field built upon clear visualizations using a unified notation and equations, lowering the barrier to entry for the reader. The accompanying website provides complementary code and hundreds of exercises with solutions.
Artificial Intelligence For Science A Deep Learning Revolution
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Author : Alok Choudhary
language : en
Publisher: World Scientific
Release Date : 2023-03-21
Artificial Intelligence For Science A Deep Learning Revolution written by Alok Choudhary and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-21 with Computers categories.
This unique collection introduces AI, Machine Learning (ML), and deep neural network technologies leading to scientific discovery from the datasets generated both by supercomputer simulation and by modern experimental facilities.Huge quantities of experimental data come from many sources — telescopes, satellites, gene sequencers, accelerators, and electron microscopes, including international facilities such as the Large Hadron Collider (LHC) at CERN in Geneva and the ITER Tokamak in France. These sources generate many petabytes moving to exabytes of data per year. Extracting scientific insights from these data is a major challenge for scientists, for whom the latest AI developments will be essential.The timely handbook benefits professionals, researchers, academics, and students in all fields of science and engineering as well as AI, ML, and neural networks. Further, the vision evident in this book inspires all those who influence or are influenced by scientific progress.
Advanced Interdisciplinary Applications Of Deep Learning For Data Science
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Author : Mathew Biju, Soly
language : en
Publisher: IGI Global
Release Date : 2024-12-18
Advanced Interdisciplinary Applications Of Deep Learning For Data Science written by Mathew Biju, Soly and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-18 with Computers categories.
Advanced interdisciplinary applications of deep learning are revolutionizing the field of data science, enabling new solutions across industries. By leveraging neural networks and datasets, deep learning techniques are transforming how businesses analyze, interpret, and gain insights from complex data. In fields like healthcare, finance, engineering, and business, deep learning models can uncover patterns and make predictions to enhance data-driven decision-making while fostering new opportunities in areas like personalized medicine, autonomous systems, and predictive analytics. As deep learning continues evolves, its interdisciplinary impact expands, creating new possibilities for solving challenges in data science. Advanced Interdisciplinary Applications of Deep Learning for Data Science explores innovations of deep learning technology in data science for various industries and sectors. It examines solutions for decision-making and patient or customer service using machine learning, AI, and predictive analytics. This book covers topics such as bioinformatics, environmental monitoring, and medical diseases, and is a useful resource for data scientists, computer engineers, medical professionals, academicians, and researchers.
Deep Learning For Physical Scientists
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Author : Edward O. Pyzer-Knapp
language : en
Publisher: John Wiley & Sons
Release Date : 2021-09-20
Deep Learning For Physical Scientists written by Edward O. Pyzer-Knapp 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 2021-09-20 with Science categories.
Discover the power of machine learning in the physical sciences with this one-stop resource from a leading voice in the field Deep Learning for Physical Scientists: Accelerating Research with Machine Learning delivers an insightful analysis of the transformative techniques being used in deep learning within the physical sciences. The book offers readers the ability to understand, select, and apply the best deep learning techniques for their individual research problem and interpret the outcome. Designed to teach researchers to think in useful new ways about how to achieve results in their research, the book provides scientists with new avenues to attack problems and avoid common pitfalls and problems. Practical case studies and problems are presented, giving readers an opportunity to put what they have learned into practice, with exemplar coding approaches provided to assist the reader. From modelling basics to feed-forward networks, the book offers a broad cross-section of machine learning techniques to improve physical science research. Readers will also enjoy: A thorough introduction to the basic classification and regression with perceptrons An exploration of training algorithms, including back propagation and stochastic gradient descent and the parallelization of training An examination of multi-layer perceptrons for learning from descriptors and de-noising data Discussions of recurrent neural networks for learning from sequences and convolutional neural networks for learning from images A treatment of Bayesian optimization for tuning deep learning architectures Perfect for academic and industrial research professionals in the physical sciences, Deep Learning for Physical Scientists: Accelerating Research with Machine Learning will also earn a place in the libraries of industrial researchers who have access to large amounts of data but have yet to learn the techniques to fully exploit that access.
Machine Learning In Biotechnology And Life Sciences
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Author : Saleh Alkhalifa
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-01-28
Machine Learning In Biotechnology And Life Sciences written by Saleh Alkhalifa 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 2022-01-28 with Mathematics categories.
Explore all the tools and templates needed for data scientists to drive success in their biotechnology careers with this comprehensive guide Key FeaturesLearn the applications of machine learning in biotechnology and life science sectorsDiscover exciting real-world applications of deep learning and natural language processingUnderstand the general process of deploying models to cloud platforms such as AWS and GCPBook Description The booming fields of biotechnology and life sciences have seen drastic changes over the last few years. With competition growing in every corner, companies around the globe are looking to data-driven methods such as machine learning to optimize processes and reduce costs. This book helps lab scientists, engineers, and managers to develop a data scientist's mindset by taking a hands-on approach to learning about the applications of machine learning to increase productivity and efficiency in no time. You'll start with a crash course in Python, SQL, and data science to develop and tune sophisticated models from scratch to automate processes and make predictions in the biotechnology and life sciences domain. As you advance, the book covers a number of advanced techniques in machine learning, deep learning, and natural language processing using real-world data. By the end of this machine learning book, you'll be able to build and deploy your own machine learning models to automate processes and make predictions using AWS and GCP. What you will learnGet started with Python programming and Structured Query Language (SQL)Develop a machine learning predictive model from scratch using PythonFine-tune deep learning models to optimize their performance for various tasksFind out how to deploy, evaluate, and monitor a model in the cloudUnderstand how to apply advanced techniques to real-world dataDiscover how to use key deep learning methods such as LSTMs and transformersWho this book is for This book is for data scientists and scientific professionals looking to transcend to the biotechnology domain. Scientific professionals who are already established within the pharmaceutical and biotechnology sectors will find this book useful. A basic understanding of Python programming and beginner-level background in data science conjunction is needed to get the most out of this book.
The Fundamentals Of Data Science Big Data Deep Learning And Machine Learning What You Need To Know About Data Science And Why It Matters
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Author : Vlad Sozonov
language : en
Publisher: Vinco Publishing
Release Date : 2019-11-21
The Fundamentals Of Data Science Big Data Deep Learning And Machine Learning What You Need To Know About Data Science And Why It Matters written by Vlad Sozonov and has been published by Vinco Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-21 with Computers categories.
Data science is no easy term to define. While there are many definitions available that point out its statistical or logical aspects, others focus on its machine learning impacts. Today only, get this Amazon book for just $19.99 for a limited time. Regularly priced at $35.99. The truth is, data science is a process that requires an understanding of multiple fields, methods, techniques, and more. Data science cannot be easily labeled because, when applied, it looks different to each person, business, or organization utilizing it. While the term may not be easy to define, what it is used for, can be used for, and approaches to it can be more easily understood. And that is precisely what this book aims to do. Scroll Up & Click to Buy Now! Here Is A Preview Of What You'll Discover...In this step-by-step book: This book will not only thoroughly go over all the skills, people, and steps involved in data science, it will also look closely at: ● What big data is and how data science came from it. ● How data has evolved, resulting in new methods for understanding it. ● How data science influenced artificial intelligence. ● How data science is used in machine learning and deep learning. ● How data science revolutionizes the way we train machines and set up neural networks. Data science, big data, machine learning, and deep learning tend to intimidate people. Many believe it is too complicated or technology-centered for them to break into these fields. This book is designed to simplify these complex areas in a way that anyone can understand the fundamentals. Whether you are just hearing about data science, are a student studying it in college, or looking to expand your career, this book has something to offer every type of data enthusiast. Order your copy today! Take action right away by purchase this book "The Fundamentals of Data Science: Big Data, Deep Learning, and Machine Learning: What you need to know about data science and why it matters.", for a limited time discount of only $19.99! Hurry Up!! Tags: ● data science quick ● data science strategy ● data science trading ● data science journal ● insight data science ● data science salary ● data science jobs ● data science espanol ● data science case study ● data science beginner guide
Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots
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Author : Dr. P. Kavitha
language : en
Publisher: Leilani Katie Publication
Release Date : 2023-12-23
Fundamentals Of Data Science Datamining Machinelearning Deeplearning And Iots written by Dr. P. Kavitha 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 2023-12-23 with Computers categories.
Dr. P. Kavitha, Associate Professor, Department of Computer Science, Sri Ramakrishna College of Arts & Science, Coimbatore, Tamil Nadu, India. Mr. P. Jayasheelan, Assistant Professor, Department of Computer Science, Sri Krishna Aditya College of arts and Science, Coimbatore, Tamil Nadu, India. Ms. C. Karpagam, Assistant Professor, Department of Computer Science with Data Analytics, Dr. N.G.P. Arts and Science College, Coimbatore, Tamil Nadu, India. Dr. K. Prabavathy, Assistant Professor, Department of Data Science and Analytics, Sree Saraswathi Thyagaraja College, Pollachi, Coimbatore, Tamil Nadu, India.
Data Science For Beginners
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Author : Russel R Russo
language : en
Publisher:
Release Date : 2020-02-02
Data Science For Beginners written by Russel R Russo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-02 with categories.
Are you fascinated by Data Science but it seems too complicated? Do you want to learn everything about Artificial Intelligence but it looks like it is an exclusive club? If this is you, please keep reading: you are in the right place, looking at the right book. SInce you are reading these lines you have probably already noticed this: Artificial Intelligence is all around you. Your smartphone that suggests you the next word you want to type, your Netflix account that recommends you the series you may like or Spotify's personalised playlists. This is how machines are learning from you in everyday life. And these examples are only the surface of this technological revolution. Everyone knows (well, almost everyone) how important Data Science is for the growth and success of the biggest tech companies, and many people know about the Machine Learning impact in science, medicine and statistics. Also, it is quite commonly known that Artificial Intelligence, Machine Learning Deep Learning, and the mastering of their most important language, Python, can offer a lot of possibilities in work and business. And you yourself are probably thinking "I surely can see that opportunity, but how can I seize it?" Well, if you kept reading so far you are on the right track to answer your question. Either if you want to start your own AI entreprise, to empower your business or to work in the greatest and most innovative companies, Artificial Intelligence is the future, and Python and Neural Networks programming is The Skill you want to have. The good news is that there is no exclusive club, you can easily (if you commit, of course) learn how to find your way around Artificial Intelligence, Data Science, Deep Learning and Machine Learning, and to do that Data Science for Beginners is the best way. In Data Science for Beginners you will discover: The most effective starting points when training deep neural nets The smartest way to approach Machine Learning What libraries are and which one is the best for you Tips and tricks for a smooth and painless journey into artificial intelligence Why decision tree is the way The TensorFlow parts that are going to make your coding life easy Why python is the best language for Machine Learning How to bring your ideas into a computer How to talk with deep neural networks How to deal with variables and data The most common myths about Machine Learning debunked Even If you don't know anything about programming, understanding Data Science is the ideal place to start. Still, if you already know something about programming but not about how to apply it to Artificial Intelligence, Data Science is what you want to understand. Download now Data Science for Beginners to start your path of Artificial Intelligence.