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Data Preparation for Machine Learning
Data preparation involves transforming raw data in to a form that can be modeled using machine learning algorithms. Cut through the equations, Greek letters, and confusion, and discover the specialized data preparation techniques that you need to know to get the most out of your data on your next project. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover how to confidently and effectively prepare your data for predictive modeling with machine learning.
Better Deep Learning
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 Time Series Forecasting
Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.
Deep Learning for Computer Vision
Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.
Deep Learning With Python
Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their power in a few lines of code using Keras, the best-of-breed applied deep learning library. In this Ebook, learn exactly how to get started and apply deep learning to your own machine learning projects.
The Political Science of the Middle East
A definitive overview of what political scientists are working on within the Middle East and North Africa.The Arab Uprisings of 2011-12 catalyzed a new wave of rigorous, deeply informed research on the politics of the Middle East and North Africa (MENA). In The Political Science of the Middle East, Marc Lynch, Jillian Schwedler, and Sean Yom present the definitive overview of this pathbreaking turn. This is a monumental stocktaking organized around a singular theme: new theorizing from the MENA has advanced the frontiers of comparative politics and international relations, and the close-range study of the region occupies a core place in mainstream political science. Its dozen chapters cover ...
Rough Justice
The seventh book in the bestselling Dan 'Spider' Shepherd series. Villains across London are being beaten, crippled and killed by vigilante cops. Crime rates are falling, but the powers that be want Dan 'Spider' Shepherd to bring the wave of rough justice to an end. Shepherd has always known that there are grey areas in the fight against crime. And that sometimes justice gets lost in the process. He has never been comfortable investigating cops, but working for the Serious Organised Crime Agency means that he has no choice. He has to go undercover with an elite group of officers who are at the sharp end of policing, risking their lives daily on the toughest streets in the Capital. But Shepherd has hard decisions of his own to make when his family is in the firing line.
Probability for Machine Learning
Probability is the bedrock of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in probability that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of probability to machine learning, Bayesian probability, entropy, density estimation, maximum likelihood, and much more.
Defeating Authoritarian Leaders in Postcommunist Countries
From 1998 to 2005, six elections took place in postcommunist Europe that had the surprising outcome of empowering the opposition and defeating authoritarian incumbents or their designated successors. Valerie J. Bunce and Sharon L. Wolchik compare these unexpected electoral breakthroughs. They draw three conclusions. First, the opposition was victorious because of the hard and creative work of a transnational network composed of local opposition and civil society groups, members of the international democracy assistance community and graduates of successful electoral challenges to authoritarian rule in other countries. Second, the remarkable run of these upset elections reflected the ability of this network to diffuse an ensemble of innovative electoral strategies across state boundaries. Finally, elections can serve as a powerful mechanism for democratic change. This is especially the case when civil society is strong, the transfer of political power is through constitutional means, and opposition leaders win with small mandates.
This Happened Here
This book examines the Trump phenomenon and presidency as fascist. Fascism here connotes not generically "bad" politics or a consolidated political-economic regime (Mussolini’s Italy or Hitler’s Germany) but a set of political, movement, and ideological traits understood within the context of the neoliberal-capitalist era. While Trump’s election defeat is a respite, the nation is far from out of the neofascist woods. Defeating the menace will require political and societal restructuring far beyond what is imagined by Democrats. This argument is developed across seven chapters that recount Trump’s assault on the 2020 election, specifically define the meaning of fascism as it is used in this book, demonstrate the neofascist nature of the Trump presidency, engage intellectual class Trumpism-fascism-denial, analyze the Trump base, root Trumpism in a longstanding and indeed founding American white nationalism, examine why Trump rose to power when he did, and suggest paths for fascism-proofing the USA.
