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Author: Alejandro Lopez-Lira
Publisher: John Wiley & Sons
ISBN: 1394242727
Category : Business & Economics
Languages : en
Pages : 278
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Book Description
Use ChatGPT to improve your analysis of stock markets and securities In The Predictive Edge: Outsmart the Market Using Generative AI and ChatGPT in Financial Forecasting, renowned AI and finance researcher Dr. Alejandro Lopez-Lira delivers an engaging and insightful new take on how to use large language models (LLMs) like ChatGPT to find new investment opportunities and make better trading decisions. In the book, you’ll learn how to interpret the outputs of LLMs to craft sounder trading strategies and incorporate market sentiment into your analyses of individual securities. In addition to a complete and accessible explanation of how ChatGPT and other LLMs work, you’ll find: Discussions of future trends in artificial intelligence and finance Strategies for implementing new and soon-to-come AI tools into your investing strategies and processes Techniques for analyzing market sentiment using ChatGPT and other AI tools A can’t-miss playbook for taking advantage of the full potential of the latest AI advancements, The Predictive Edge is a fully to-date and exciting exploration of the intersection of tech and finance. It will earn a place on the bookshelves of individual and professional investors everywhere.
Author: Alejandro Lopez-Lira
Publisher: John Wiley & Sons
ISBN: 1394242727
Category : Business & Economics
Languages : en
Pages : 278
Get Book Here
Book Description
Use ChatGPT to improve your analysis of stock markets and securities In The Predictive Edge: Outsmart the Market Using Generative AI and ChatGPT in Financial Forecasting, renowned AI and finance researcher Dr. Alejandro Lopez-Lira delivers an engaging and insightful new take on how to use large language models (LLMs) like ChatGPT to find new investment opportunities and make better trading decisions. In the book, you’ll learn how to interpret the outputs of LLMs to craft sounder trading strategies and incorporate market sentiment into your analyses of individual securities. In addition to a complete and accessible explanation of how ChatGPT and other LLMs work, you’ll find: Discussions of future trends in artificial intelligence and finance Strategies for implementing new and soon-to-come AI tools into your investing strategies and processes Techniques for analyzing market sentiment using ChatGPT and other AI tools A can’t-miss playbook for taking advantage of the full potential of the latest AI advancements, The Predictive Edge is a fully to-date and exciting exploration of the intersection of tech and finance. It will earn a place on the bookshelves of individual and professional investors everywhere.
Author: Leslie Ries
Publisher:
ISBN:
Category : Birds
Languages : en
Pages : 304
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Book Description
Author: Hiren Kumar Thakkar
Publisher: Springer Nature
ISBN: 3031180348
Category : Computers
Languages : en
Pages : 252
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Book Description
This book covers the relationship of recent technologies (such as Blockchain, IoT, and 5G) with the cloud computing as well as fog computing, and mobile edge computing. The relationship will not be limited to only architecture proposal, trends, and technical advancements. However, the book also explores the possibility of predictive analytics in cloud computing with respect to Blockchain, IoT, and 5G. The recent advancements in the internet-supported distributed computing i.e. cloud computing, has made it possible to process the bulk amount of data in a parallel and distributed. This has made it a lucrative technology to process the data generated from technologies such as Blockchain, IoT, and 5G. However, there are several issues a Cloud Service Provider (CSP) encounters, such as Blockchain security in cloud, IoT elasticity and scalability management in cloud, Service Level Agreement (SLA) compliances for 5G, Resource management, Load balancing, and Fault-tolerance. This edited book will discuss the aforementioned issues in connection with Blockchain, IoT, and 5G. Moreover, the book discusses how the cloud computing is not sufficient and one needs to use fog computing, and edge computing to efficiently process the data generated from IoT, and 5G. Moreover, the book shows how smart city, smart healthcare system, and smart communities are few of the most relevant IoT applications where fog computing plays a significant role. The book discusses the limitation of fog computing and the need for the edge computing to further reduce the network latency to process streaming data from IoT devices. The book also explores power of predictive analytics of Blockchain, IoT, and 5G data in cloud computing with its sister technologies. Since, the amount of resources increases day-by day, artificial intelligence (AI) tools are becoming more popular due to their capability which can be used in solving wide variety of issues, such as minimize the energy consumption of physical servers, optimize the service cost, improve the quality of experience, increase the service availability, efficiently handle the huge data flow, manages the large number of IoT devices, etc.
Author: Paul D. McNelis
Publisher: Academic Press
ISBN: 0124859674
Category : Business & Economics
Languages : en
Pages : 262
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Book Description
This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website
Author: Natascha Sabrina Harth
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Andrew Pearson
Publisher: Createspace Independent Publishing Platform
ISBN: 9781979079525
Category :
Languages : en
Pages : 404
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Book Description
The Predictive Retailer is a retail company that utilizes the latest technological developments to deliver an exceptional personalized experience to each and every customer. Today, technology such as AI, Machine Learning, Augmented Reality, IoT, Real-time stream processing, social media, and wearables are altering the Customer Experience (CX) landscape and retailers need to jump aboard this fast moving technology or run the risk of being left out in the cold. The Predictive Retailer reveals how these and other technologies can help shape the customer journey. The book details how the five types of analytics-descriptive, diagnostic, predictive, prescriptive, and edge analytics-affect not only the customer journey, but also just about every operating function of the retailer. An IoT connected retailer can make its operations smart. Connected devices can help with inventory optimization, supply chain management, labor management, waste management, as well as keep the retailer's data centers green and its energy use smart. Social media is no longer a vanity platform, but rather it is a place to both connect with current customers as well as court new ones. It is also a powerful branding channel that can be utilized to both understand a retailer's position in the market, as well as a place to benchmark its position against its competitors. Today, technology moves at break-neck speed and it can offer the potential of anticipatory capabilities, but it also comes with a confusing variety of technological terms--Big Data, Cognitive Computing, CX, Data Lakes, Hadoop, Kafka, Personalization, Spark, etc., etc. The Predictive Retailer will help make sense of it all, so that a retail executive can cut through the confusing technological jargon and understand why a Spark-based real-time stream processing data stream might be preferable to a TIBCO Streambase one, or an IBM Streaming Analytics one. This book will help retail executives break through the technological clutter so that they can deliver an unrivaled customer experience to each and every patron that comes through their doors.
Author: Paul D. McNelis
Publisher: Elsevier
ISBN: 0080479650
Category : Computers
Languages : en
Pages : 261
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Book Description
This book explores the intuitive appeal of neural networks and the genetic algorithm in finance. It demonstrates how neural networks used in combination with evolutionary computation outperform classical econometric methods for accuracy in forecasting, classification and dimensionality reduction. McNelis utilizes a variety of examples, from forecasting automobile production and corporate bond spread, to inflation and deflation processes in Hong Kong and Japan, to credit card default in Germany to bank failures in Texas, to cap-floor volatilities in New York and Hong Kong. * Offers a balanced, critical review of the neural network methods and genetic algorithms used in finance * Includes numerous examples and applications * Numerical illustrations use MATLAB code and the book is accompanied by a website
Author: Sidney Shek
Publisher: Lulu.com
ISBN: 057809424X
Category : Computers
Languages : en
Pages : 72
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Book Description
Data has become a factor of production, like labor and steel, and is driving a new data-centered economy. The Data rEvolution is about data volume, variety, velocity and value. It is about new ways to organize and manage data for rapid processing using tools like Hadoop and MapReduce. It is about the explosion of new tools for "connecting the dots" and increasing knowledge, including link analysis, temporal analysis and predictive analytics. It is about a vision of "analytics for everyone" that puts sophisticated statistics into the hands of all. And, it is about using visual analytics to parse the data and literally see new relationships and insights on the fly. As the data and tools become democratized, we will see a new world of experimentation and creative problem-solving, where data comes from both inside and outside the organization. Your own data is not enough. This report is a must-read for IT and business leaders who want to maximize the value of data for their organization.
Author: Joao Gama
Publisher: Springer Nature
ISBN: 3030667707
Category : Computers
Languages : en
Pages : 317
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Book Description
This book constitutes selected papers from the Second International Workshop on IoT Streams for Data-Driven Predictive Maintenance, IoT Streams 2020, and First International Workshop on IoT, Edge, and Mobile for Embedded Machine Learning, ITEM 2020, co-located with ECML/PKDD 2020 and held in September 2020. Due to the COVID-19 pandemic the workshops were held online. The 21 full papers and 3 short papers presented in this volume were thoroughly reviewed and selected from 35 submissions and are organized according to the workshops and their topics: IoT Streams 2020: Stream Learning; Feature Learning; ITEM 2020: Unsupervised Machine Learning; Hardware; Methods; Quantization.
Author: Eric Siegel
Publisher: John Wiley & Sons
ISBN: 1119153654
Category : Business & Economics
Languages : en
Pages : 368
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Book Description
"Mesmerizing & fascinating..." —The Seattle Post-Intelligencer "The Freakonomics of big data." —Stein Kretsinger, founding executive of Advertising.com Award-winning | Used by over 30 universities | Translated into 9 languages An introduction for everyone. In this rich, fascinating — surprisingly accessible — introduction, leading expert Eric Siegel reveals how predictive analytics (aka machine learning) works, and how it affects everyone every day. Rather than a “how to” for hands-on techies, the book serves lay readers and experts alike by covering new case studies and the latest state-of-the-art techniques. Prediction is booming. It reinvents industries and runs the world. Companies, governments, law enforcement, hospitals, and universities are seizing upon the power. These institutions predict whether you're going to click, buy, lie, or die. Why? For good reason: predicting human behavior combats risk, boosts sales, fortifies healthcare, streamlines manufacturing, conquers spam, optimizes social networks, toughens crime fighting, and wins elections. How? Prediction is powered by the world's most potent, flourishing unnatural resource: data. Accumulated in large part as the by-product of routine tasks, data is the unsalted, flavorless residue deposited en masse as organizations churn away. Surprise! This heap of refuse is a gold mine. Big data embodies an extraordinary wealth of experience from which to learn. Predictive analytics (aka machine learning) unleashes the power of data. With this technology, the computer literally learns from data how to predict the future behavior of individuals. Perfect prediction is not possible, but putting odds on the future drives millions of decisions more effectively, determining whom to call, mail, investigate, incarcerate, set up on a date, or medicate. In this lucid, captivating introduction — now in its Revised and Updated edition — former Columbia University professor and Predictive Analytics World founder Eric Siegel reveals the power and perils of prediction: What type of mortgage risk Chase Bank predicted before the recession. Predicting which people will drop out of school, cancel a subscription, or get divorced before they even know it themselves. Why early retirement predicts a shorter life expectancy and vegetarians miss fewer flights. Five reasons why organizations predict death — including one health insurance company. How U.S. Bank and Obama for America calculated the way to most strongly persuade each individual. Why the NSA wants all your data: machine learning supercomputers to fight terrorism. How IBM's Watson computer used predictive modeling to answer questions and beat the human champs on TV's Jeopardy! How companies ascertain untold, private truths — how Target figures out you're pregnant and Hewlett-Packard deduces you're about to quit your job. How judges and parole boards rely on crime-predicting computers to decide how long convicts remain in prison. 182 examples from Airbnb, the BBC, Citibank, ConEd, Facebook, Ford, Google, the IRS, LinkedIn, Match.com, MTV, Netflix, PayPal, Pfizer, Spotify, Uber, UPS, Wikipedia, and more. How does predictive analytics work? This jam-packed book satisfies by demystifying the intriguing science under the hood. For future hands-on practitioners pursuing a career in the field, it sets a strong foundation, delivers the prerequisite knowledge, and whets your appetite for more. A truly omnipresent science, predictive analytics constantly affects our daily lives. Whether you are a
