Name: Machine Learning for Economics and Finance in TensorFlow 2: Deep Learning Models for Research and Industry
ISBN: 9781484263723

Book information

Authors: Isaiah Hull verified identity
First published: 2020
Editions known: 2
Publishers: Apress
Languages: eng
ISBN-13: 9781484263723, 9781484263730
Main topics: Deep Learning for Finance
Also covers: Financial Machine Learning
Related site topics: Machine Learning for Market Forecasting, NLP & LLMs in Finance

Overview

Machine Learning for Economics and Finance in TensorFlow 2 is a book by Isaiah Hull, first published in 2020. In this catalogue it is classified mainly under Deep Learning for Finance, with secondary coverage of Financial Machine Learning.

Audience and depth. The available metadata did not allow a mathematical difficulty estimate, so none is shown; treat the technical level as unknown.

Orientation. The theory-versus-practice balance could not be determined from metadata. The archive holds 6 papers whose topics and vocabulary overlap with this book; those links are inferred (see the research connections below).

How to read this page. Topics, difficulty, prerequisites and orientation are model-derived (rule-based, rule_based_v1) from bibliographic metadata such as title, subject headings and edition data. They were not produced by reading the book and are not a review. Relevance confidence is 57% and difficulty confidence is 0%; the catalogue lists no ratings or awards.

Research assessment

Rule-based and model-derived from metadata (title, subject headings, edition data). These are not reviews or ratings; see the evidence below.

Quant-finance relevance	40/100 confidence 57% Score 39.9/100. Strongest: quant_relevance 0.38, metadata_completeness 0.85; weakest: practical_applicability 0.00. Evidence: title:'finance'. Difficulty unknown (neutral technical_depth).
Mathematical difficulty	Unknown
Metadata quality	65%

Difficulty evidence (2 signals)

machine_learning matched in subtitle: “deep learning”
machine_learning matched in title: “machine learning”

Research connections

Related papers on this site

Similarity of research area (shared vocabulary, topics and methods). Not citations: the paper does not necessarily cite this book.

Quantitative Financial Modeling for Sri Lankan Markets: Approach Combining NLP, Clustering and Time-Series Forecasting Related research area inferred similarity 0.55
Finance-Grounded Optimization For Algorithmic Trading Topic similarity inferred similarity 0.51
A compendium of data sources for data science, machine learning, and artificial intelligence Topic similarity inferred similarity 0.50
The Role of AI in Financial Forecasting: ChatGPT's Potential and Challenges Topic similarity inferred similarity 0.46
From Deep Learning to LLMs: A survey of AI in Quantitative Investment Related research area inferred similarity 0.46
Stochastic Delay Differential Games: Financial Modeling and Machine Learning Algorithms Topic similarity inferred similarity 0.45

Methods covered

Deep Learning inferred
Machine Learning (Non-Deep) inferred

Similar books

Neural Networks in Finance and Investing inferred similarity 0.49
Neural networks and the financial markets inferred similarity 0.48
Neural Networks in Finance inferred similarity 0.48
Neural networks for financial forecasting inferred similarity 0.44
Machine Learning in Finance inferred similarity 0.43

Author profiles

Isaiah Hull verified identity

External resources

Open Library
DOI
Search on Amazon (ISBN-13 9781484263730) (search link; may be an affiliate link)

Relationship graph

Solid lines are verified facts (authorship from persistent identifiers, editions); dashed lines are inferred by rules or similarity. Open in the full explorer.

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