Iterations of Loss - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Iterations of Loss write by Jeffrey Sacks. This book was released on 2015-02-25. Iterations of Loss available in PDF, EPUB and Kindle. In a series of exquisite close readings of Arabic and Arab Jewish writing, Jeffrey Sacks considers the relation of poetic statement to individual and collective loss, the dispossession of peoples and languages, and singular events of destruction in the nineteenth, twentieth, and twenty-first centuries. Addressing the work of Mahmoud Darwish, Ahmad Faris al-Shidyaq, Elias Khoury, Edmond Amran El Maleh, Shimon Ballas, and Taha Husayn, Sacks demonstrates the reiterated incursion of loss into the time of life—losses that language declines to mourn. Language occurs as the iteration of loss, confounding its domestication in the form of the monolingual state in the Arabic nineteenth century’s fallout. Reading the late lyric poetry of the Palestinian poet Mahmoud Darwish in relation to the destruction of Palestine in 1948, Sacks reconsiders the nineteenth century Arabic nahda and its relation to colonialism, philology, and the European Enlightenment. He argues that this event is one of catastrophic loss, wherein the past suddenly appears as if it belonged to another time. Reading al-Shidyaq’s al-Saq ‘ala al-saq (1855) and the legacies to which it points in post-1948 writing in Arabic, Hebrew, and French, Sacks underlines a displacement and relocation of the Arabic word adab and its practice, offering a novel contribution to Arabic and Middle East Studies, critical theory, poetics, aesthetics, and comparative literature. Drawing on writings of Jacques Derrida, Walter Benjamin, Avital Ronell, Judith Butler, Theodor Adorno, and Edward W. Said, Iterations of Loss shows that language interrupts its pacification as an event of aesthetic coherency, to suggest that literary comparison does not privilege a renewed giving of sense but gives place to a new sense of relation.
Programming Machine Learning
Programming Machine Learning - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Programming Machine Learning write by Paolo Perrotta. This book was released on 2020-03-31. Programming Machine Learning available in PDF, EPUB and Kindle. You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool. But where to start? It's easy to be intimidated, even as a software developer. The good news is that it doesn't have to be that hard. Master machine learning by writing code one line at a time, from simple learning programs all the way to a true deep learning system. Tackle the hard topics by breaking them down so they're easier to understand, and build your confidence by getting your hands dirty. Peel away the obscurities of machine learning, starting from scratch and going all the way to deep learning. Machine learning can be intimidating, with its reliance on math and algorithms that most programmers don't encounter in their regular work. Take a hands-on approach, writing the Python code yourself, without any libraries to obscure what's really going on. Iterate on your design, and add layers of complexity as you go. Build an image recognition application from scratch with supervised learning. Predict the future with linear regression. Dive into gradient descent, a fundamental algorithm that drives most of machine learning. Create perceptrons to classify data. Build neural networks to tackle more complex and sophisticated data sets. Train and refine those networks with backpropagation and batching. Layer the neural networks, eliminate overfitting, and add convolution to transform your neural network into a true deep learning system. Start from the beginning and code your way to machine learning mastery. What You Need: The examples in this book are written in Python, but don't worry if you don't know this language: you'll pick up all the Python you need very quickly. Apart from that, you'll only need your computer, and your code-adept brain.
Distributed Energy Management of Electrical Power Systems
Distributed Energy Management of Electrical Power Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Distributed Energy Management of Electrical Power Systems write by Yinliang Xu. This book was released on 2021-01-13. Distributed Energy Management of Electrical Power Systems available in PDF, EPUB and Kindle. Go in-depth with this comprehensive discussion of distributed energy management Distributed Energy Management of Electrical Power Systems provides the most complete analysis of fully distributed control approaches and their applications for electric power systems available today. Authored by four respected leaders in the field, the book covers the technical aspects of control, operation management, and optimization of electric power systems. In each chapter, the book covers the foundations and fundamentals of the topic under discussion. It then moves on to more advanced applications. Topics reviewed in the book include: System-level coordinated control Optimization of active and reactive power in power grids The coordinated control of distributed generation, elastic load and energy storage systems Distributed Energy Management incorporates discussions of emerging and future technologies and their potential effects on electrical power systems. The increased impact of renewable energy sources is also covered. Perfect for industry practitioners and graduate students in the field of power systems, Distributed Energy Management remains the leading reference for anyone with an interest in its fascinating subject matter.
Transactions on Intelligent Welding Manufacturing
Transactions on Intelligent Welding Manufacturing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Transactions on Intelligent Welding Manufacturing write by Shanben Chen. This book was released on 2020-11-18. Transactions on Intelligent Welding Manufacturing available in PDF, EPUB and Kindle. The primary aim of this volume is to provide researchers and engineers from both academic and industry with up-to-date coverage of new results in the field of robotic welding, intelligent systems and automation. The book is mainly based on papers selected from the 2019 International Workshop on Intelligentized Welding Manufacturing (IWIWM’2019) in USA. The articles show that the intelligentized welding manufacturing (IWM) is becoming an inevitable trend with the intelligentized robotic welding as the key technology. The volume is divided into four logical parts: Intelligent Techniques for Robotic Welding, Sensing of Arc Welding Processing, Modeling and Intelligent Control of Welding Processing, as well as Intelligent Control and its Applications in Engineering.
Deep Learning for Natural Language Processing
Deep Learning for Natural Language Processing - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Deep Learning for Natural Language Processing write by Palash Goyal. This book was released on 2018-06-26. Deep Learning for Natural Language Processing available in PDF, EPUB and Kindle. Discover the concepts of deep learning used for natural language processing (NLP), with full-fledged examples of neural network models such as recurrent neural networks, long short-term memory networks, and sequence-2-sequence models. You’ll start by covering the mathematical prerequisites and the fundamentals of deep learning and NLP with practical examples. The first three chapters of the book cover the basics of NLP, starting with word-vector representation before moving onto advanced algorithms. The final chapters focus entirely on implementation, and deal with sophisticated architectures such as RNN, LSTM, and Seq2seq, using Python tools: TensorFlow, and Keras. Deep Learning for Natural Language Processing follows a progressive approach and combines all the knowledge you have gained to build a question-answer chatbot system. This book is a good starting point for people who want to get started in deep learning for NLP. All the code presented in the book will be available in the form of IPython notebooks and scripts, which allow you to try out the examples and extend them in interesting ways. What You Will Learn Gain the fundamentals of deep learning and its mathematical prerequisites Discover deep learning frameworks in Python Develop a chatbot Implement a research paper on sentiment classification Who This Book Is For Software developers who are curious to try out deep learning with NLP.
