Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Machine Learning for Algorithmic Trading
Leverage machine learning to design and back-test automated trading strategies for real-world markets using pandas, TA-Lib, scikit-learn, LightGBM, SpaCy, Gensim, TensorFlow 2, Zipline, backtrader, Alphalens, and pyfolio. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesDesign, train, and evaluate machine learning algorithms that underpin automated trading strategiesCreate a research and strategy development process to apply predictive modeling to trading decisionsLeverage NLP and deep learning to extract tradeable signals from market and alternative dataBook Description The explosive growth of digital data has boosted the demand for expertise in trad...
Hands-On Machine Learning for Algorithmic Trading
Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key FeaturesImplement machine learning algorithms to build, train, and validate algorithmic modelsCreate your own algorithmic design process to apply probabilistic machine learning approaches to trading decisionsDevelop neural networks for algorithmic trading to perform time series forecasting and smart analyticsBook Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of dat...
Python for Finance
A hands-on guide with easy-to-follow examples to help you learn about option theory, quantitative finance, financial modeling, and time series using Python. Python for Finance is perfect for graduate students, practitioners, and application developers who wish to learn how to utilize Python to handle their financial needs. Basic knowledge of Python will be helpful but knowledge of programming is necessary.
Engineering MLOps
Get up and running with machine learning life cycle management and implement MLOps in your organization Key FeaturesBecome well-versed with MLOps techniques to monitor the quality of machine learning models in productionExplore a monitoring framework for ML models in production and learn about end-to-end traceability for deployed modelsPerform CI/CD to automate new implementations in ML pipelinesBook Description Engineering MLps presents comprehensive insights into MLOps coupled with real-world examples in Azure to help you to write programs, train robust and scalable ML models, and build ML pipelines to train and deploy models securely in production. The book begins by familiarizing you wit...
Possessed
Silent cinema and contemporaneous literature explored themes of mesmerism, possession, and the ominous agency of corporate bodies that subsumed individual identities. At the same time, critics accused film itself of exerting a hypnotic influence over spellbound audiences. Stefan Andriopoulos shows that all this anxiety over being governed by an outside force was no marginal oddity, but rather a pervasive concern in the late nineteenth and early twentieth centuries. Tracing this preoccupation through the period’s films—as well as its legal, medical, and literary texts—Andriopoulos pays particular attention to the terrifying notion of murder committed against one’s will. He returns us ...
Yearnings in the Meantime
Shortly after the book’s protagonists moved into their apartment complex in Sarajevo, they, like many others, were overcome by the 1992-1995 war and the disintegration of socialist Yugoslavia More than a decade later, in post-war Bosnia and Herzegovina, they felt they were collectively stuck in a time warp where nothing seemed to be as it should be. Starting from everyday concerns, this book paints a compassionate yet critical portrait of people’s sense that they were in limbo, trapped in a seemingly endless “Meantime.” Ethnographically investigating yearnings for “normal lives” in the European semi-periphery, it proposes fresh analytical tools to explore how the time and place in which we are caught shape our hopes and fears.
Financial Market Regulation and Reforms in Emerging Markets
A Brookings Institution Press and Asian Development Bank Institute publication The rapid spread and far-reaching impact of the global financial crisis have highlighted the need for strengthening financial systems in advanced economies and emerging markets. Emerging markets face particular challenges in developing their nascent financial systems and making them resilient to domestic and external shocks. Financial reforms are critical to these economies as they pursue programs of high and sustainable growth. In this timely volume Masahiro Kawai, Eswar Prasad, and their contributors offer a systematic overview of recent developments in—and the latest thinking about—regulatory frameworks in ...
Advances in Financial Machine Learning
Learn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Fundamentals of Clinical Data Science
This open access book comprehensively covers the fundamentals of clinical data science, focusing on data collection, modelling and clinical applications. Topics covered in the first section on data collection include: data sources, data at scale (big data), data stewardship (FAIR data) and related privacy concerns. Aspects of predictive modelling using techniques such as classification, regression or clustering, and prediction model validation will be covered in the second section. The third section covers aspects of (mobile) clinical decision support systems, operational excellence and value-based healthcare. Fundamentals of Clinical Data Science is an essential resource for healthcare professionals and IT consultants intending to develop and refine their skills in personalized medicine, using solutions based on large datasets from electronic health records or telemonitoring programmes. The book’s promise is “no math, no code”and will explain the topics in a style that is optimized for a healthcare audience.
Machine Learning for Financial Risk Management with Python
Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll learn how to compare results from ML models with results obtained by traditional financial risk models. Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models. Review classical time series applications and compare them with deep learning models Explore volatility modeling to measure degrees of risk, using ...
