Although the non-profit industry has advanced using CRMs and donor databases, it has not fully explored the data stored in those databases. Data Science for Fundraising will help you generate data-driven results and effective solutions for several challenges in your non-profit. Discover the techniques used by the top R programmers.
Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and Deepnet Key FeaturesUnderstand deep learning algorithms and architectures using R and determine which algorithm is best suited for a specific problemImprove models using parameter tuning, feature engineering, and ensemblingApply advanced neural network models such as deep autoencoders and generative adversarial networks (GANs) across different domainsBook Description Deep learning enables efficient and accurate learning from a massive amount of data. This book will help you overcome a number of challenges using various deep learning algorithms and architectures with R programming. This book starts with a brief overview of machine learning and deep learning and how to build your first neural network. You’ll understand the architecture of various deep learning algorithms and their applicable fields, learn how to build deep learning models, optimize hyperparameters, and evaluate model performance. Various deep learning applications in image processing, natural language processing (NLP), recommendation systems, and predictive analytics will also be covered. Later chapters will show you how to tackle recognition problems such as image recognition and signal detection, programmatically summarize documents, conduct topic modeling, and forecast stock market prices. Toward the end of the book, you will learn the common applications of GANs and how to build a face generation model using them. Finally, you’ll get to grips with using reinforcement learning and deep reinforcement learning to solve various real-world problems. By the end of this deep learning book, you will be able to build and deploy your own deep learning applications using appropriate frameworks and algorithms. What you will learnDesign a feedforward neural network to see how the activation function computes an outputCreate an image recognition model using convolutional neural networks (CNNs)Prepare data, decide hidden layers and neurons and train your model with the backpropagation algorithmApply text cleaning techniques to remove uninformative text using NLPBuild, train, and evaluate a GAN model for face generationUnderstand the concept and implementation of reinforcement learning in RWho this book is for This book is for data scientists, machine learning engineers, and deep learning developers who are familiar with machine learning and are looking to enhance their knowledge of deep learning using practical examples. Anyone interested in increasing the efficiency of their machine learning applications and exploring various options in R will also find this book useful. Basic knowledge of machine learning techniques and working knowledge of the R programming language is expected.
Explore and implement deep learning to solve various real-world problems using modern R libraries such as TensorFlow, MXNet, H2O, and Deepnet Key FeaturesUnderstand deep learning algorithms and architectures using R and determine which algorithm is best suited for a specific problemImprove models using parameter tuning, feature engineering, and ensemblingApply advanced neural network models such as deep autoencoders and generative adversarial networks (GANs) across different domainsBook Description Deep learning enables efficient and accurate learning from a massive amount of data. This book will help you overcome a number of challenges using various deep learning algorithms and architectures with R programming. This book starts with a brief overview of machine learning and deep learning and how to build your first neural network. You’ll understand the architecture of various deep learning algorithms and their applicable fields, learn how to build deep learning models, optimize hyperparameters, and evaluate model performance. Various deep learning applications in image processing, natural language processing (NLP), recommendation systems, and predictive analytics will also be covered. Later chapters will show you how to tackle recognition problems such as image recognition and signal detection, programmatically summarize documents, conduct topic modeling, and forecast stock market prices. Toward the end of the book, you will learn the common applications of GANs and how to build a face generation model using them. Finally, you’ll get to grips with using reinforcement learning and deep reinforcement learning to solve various real-world problems. By the end of this deep learning book, you will be able to build and deploy your own deep learning applications using appropriate frameworks and algorithms. What you will learnDesign a feedforward neural network to see how the activation function computes an outputCreate an image recognition model using convolutional neural networks (CNNs)Prepare data, decide hidden layers and neurons and train your model with the backpropagation algorithmApply text cleaning techniques to remove uninformative text using NLPBuild, train, and evaluate a GAN model for face generationUnderstand the concept and implementation of reinforcement learning in RWho this book is for This book is for data scientists, machine learning engineers, and deep learning developers who are familiar with machine learning and are looking to enhance their knowledge of deep learning using practical examples. Anyone interested in increasing the efficiency of their machine learning applications and exploring various options in R will also find this book useful. Basic knowledge of machine learning techniques and working knowledge of the R programming language is expected.
Why was it that, across Scotland over the last two and a half centuries, architectural monuments were raised to national heroes? Were hero buildings commissioned as manifestations of certain social beliefs, or as a built environmental form of social advocacy? And if so, then how and why were social aims and intentions translated into architectural form, and how effective were they? A tradition of building architectural monuments to commemorate national heroes developed as a distinctive feature of the Scottish built environment. As concrete manifestations of powerful social and political currents of thought and opinion, these hero buildings make important statements about identity, the nation and social history. The book examines this architectural culture by studying a prominent selection of buildings, such as the Burns monuments in Alloway, Edinburgh and Kilmarnock, the Edinburgh Scott Monument, the Glenfinnan Monument and the Wallace Monument in Stirling. They give testimony to how a variety of architectural forms and styles can be adapted through time to bear particular social messages of symbolic weight. This tradition, which literally allows us to dwell on important social issues of the past, has been somewhat neglected in serious architectural history and heritage, and indeed one of the main monuments has already been destroyed. By raising awareness of this rich architectural and social heritage, while analysing and interpreting the buildings in their historical context, this book makes an exciting and original scholarly contribution to the current debates on identity and nationality taking place in Scotland and the wider UK.
Nearly fifty years after his death, Albert Einstein remains one of America's foremost cultural icons. A thicket of materials, ranging from scholarly to popular, have been written, compiled, produced, and published about his life and his teachings. Among the ocean of Einsteinia-scientific monographs, biographies, anthologies, bibliographies, calendars, postcards, posters, and Hollywood films-however, there is a peculiar void when it comes to the connection that the brilliant scientist had with the African American community. Nowhere is there any mention of his close relationship with Paul Robeson, despite Einstein's close friendship with him, or W.E.B. Du Bois, despite Einstein's support for him. This unique volume is the first to bring together a wealth of writings by the scientist on the topic of race. Although his activism in this area is less well known than his efforts on behalf of international peace and scientific cooperation, Einstein spoke out vigorously against racism both in the United States and around the world. Fred Jerome and Rodger Taylor suggest that one explanation for this historical amnesia is that Einstein's biographers avoided "controversial" topics, such as his friendships with African Americans and his political activities, including his involvement as co-chair of an antilynching campaign, fearing that mention of these details may tarnish the feel-good impression his image lends topics of science, history, and America. Combining the scientist's letters, speeches, and articles with engaging narrative and historical discussions that place his public statements in the context of his life and times, this important collection not only brings attention to Einstein's antiracist public activities, but also provides insight into the complexities of antiracist culture in America. The volume also features a selection of candid interviews with African Americans who knew Einstein as children. For a man whose words and reflections have influenced so many, it is long overdue that Einstein's thoughts on this vital topic are made easily accessible to the general public.
A celestial navigation book unlike any other, including understanding lunar distances. This book is dedicated simply to removing the cloak of mystery; to teach the concepts, some interesting history, the techniques, and computational methods using the simple pocket scientific calculator. And yes, also how to build your own navigational tools. Included in the appendix are S-tables and work sheets to do your own sight reduction without computers or calculators. At my web site (http: //www.teacupnavigation.net) is free celestial nav software to download. You will enjoy this software!
State intervention in family life is an important and problematic political and social issue, and one which is surrounded by debates of a highly ideological nature. The central theme of this valuable book is that of 'family life' as an object of both social policy interest and welfare intervention. The author applies a sociological perspective on social control to a range of issues exciting public and political debate; amongst them, marriage conciliation, community care, lone parenthood and underclass status, and child abuse.
A comprehensive account of Indian-white relations throughout Canada's history. Miller charts the deterioration of the relationship from the initial, mutually beneficial contact in the fur trade to the current impasse.
This is Rodger C. Gibbs's testimony of his religious awakening, an account of how he became an active Christian. In the mid-1980s, in response to a calling, he gave up his job and devoted his life to the service of God, a move that surprised and puzzled many around him, including his family. Prompted to record the development of his devotion, he wrote this book in an attempt to share with others the joy that his life change has brought upon him. He has studied the Bible carefully and conscientiously and the result of his new learning is evident throughout his work.
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