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Applications of Machine Learning and AI in Banking and Finance in 2023

Analytics Vidhya

Introduction Could the American recession of 2008-10 have been avoided if machine learning and artificial intelligence had been used to anticipate the stock market, identify hazards, or uncover fraud? The recent advancements in the banking and finance sector suggest an affirmative response to this question.

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Getting Started with AI

Towards AI

As a reminder, I highly recommend that you refer to more than one resource (other than documentation) when learning ML, preferably a textbook geared toward your learning level (beginner/intermediate / advanced). In ML, there are a variety of algorithms that can help solve problems. I also have a medium article on AI Learning Resources.

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Two Indispensable Tools for Measuring the Quality of AI Systems

ODSC - Open Data Science

Measuring the quality of free text responses is not trivial compared to traditional ML models and requires semantic comparisons to approach parity with human evaluation. David received his BS in Mechanical Engineering in 2001 from Ohio Northern University and his PhD in Biomedical Engineering in 2008 from the University of Virginia.

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1

AWS Machine Learning Blog

Machine learning (ML) presents an opportunity to address some of these concerns and is being adopted to advance data analytics and derive meaningful insights from diverse HCLS data for use cases like care delivery, clinical decision support, precision medicine, triage and diagnosis, and chronic care management.

AWS 104
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Reinventing the data experience: Use generative AI and modern data architecture to unlock insights

AWS Machine Learning Blog

Solution overview A modern data architecture on AWS applies artificial intelligence and natural language processing to query multiple analytics databases. Sales & Marketing Amazon RedShift What was the total commission for the ticket sales in the year 2008? Sovik Kumar Nath is an AI/ML solution architect with AWS.

Database 101
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Structural Evolutions in Data

O'Reilly Media

” Consider the structural evolutions of that theme: Stage 1: Hadoop and Big Data By 2008, many companies found themselves at the intersection of “a steep increase in online activity” and “a sharp decline in costs for storage and computing.” And it (wisely) stuck to implementations of industry-standard algorithms.

Hadoop 137
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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). And finally, some activities, such as those involved with the latest advances in artificial intelligence (AI), are simply not practically possible, without hardware acceleration. Work by Hinton et al.

AWS 116