https://insideainews.com/category/resources/book-reviews/ Illuminating AI's Frontiers: Your Go-To News Destination. Tue, 14 May 2024 16:29:48 +0000 en-US hourly 1 https://wordpress.org/?v=6.6.1 https://insideainews.com/wp-content/uploads/2024/06/iain-favicon.png https://insideainews.com/category/resources/book-reviews/ 32 32 136462205 https://insideainews.com/2024/05/13/book-excerpt-data-technology-and-algorithms/ https://insideainews.com/2024/05/13/book-excerpt-data-technology-and-algorithms/#respond Mon, 13 May 2024 10:00:00 +0000 https://insidebigdata.com/?p=35273 The following is excerpted from Data Rules: Reinventing the Market Economy by Cristina Alaimo and Jannis Kallinikos. Reprinted with permission from The MIT Press. Copyright 2024.]]> https://insideainews.com/2024/05/13/book-excerpt-data-technology-and-algorithms/feed/ 0 35273 https://insideainews.com/2024/04/16/avoid-these-7-common-business-related-mistakes-on-data-projects/ https://insideainews.com/2024/04/16/avoid-these-7-common-business-related-mistakes-on-data-projects/#respond Tue, 16 Apr 2024 10:00:00 +0000 https://insidebigdata.com/?p=35134 This article is excerpted from the book, “Winning with Data Science: A Handbook for Business Leaders,” by Howard Friedman and Akshay Swaminathan with permission from the publisher, Columbia Business School Publishing. The article covers how to avoid 7 common business-related mistakes on data projects that all stem from failures in planning, preparation and communication. ]]> https://insideainews.com/2024/04/16/avoid-these-7-common-business-related-mistakes-on-data-projects/feed/ 0 35134 https://insideainews.com/2024/01/22/book-review-a-hands-on-introduction-to-machine-learning/ https://insideainews.com/2024/01/22/book-review-a-hands-on-introduction-to-machine-learning/#respond Mon, 22 Jan 2024 11:00:00 +0000 https://insidebigdata.com/?p=34596 I was pleased to receive a review copy of this new title from Cambridge University Press, "A Hands-on Introduction to Machine Learning." The hardcover book is very attractive, well-produced and solid! It will weigh down your backpack for sure. As a university instructor myself, I immediately appreciated author and University of Washington professor Chirag Shah's pedagogical approach. ]]> https://insideainews.com/2024/01/22/book-review-a-hands-on-introduction-to-machine-learning/feed/ 0 34596 https://insideainews.com/2023/10/02/what-does-the-commercialization-of-generative-ai-mean-for-society/ https://insideainews.com/2023/10/02/what-does-the-commercialization-of-generative-ai-mean-for-society/#respond Mon, 02 Oct 2023 10:00:00 +0000 https://insidebigdata.com/?p=33544 ACM, the Association for Computing Machinery has released "TechBrief: Generative Artificial Intelligence.” It is the latest in the quarterly ACM TechBriefs series of short technical bulletins that present scientifically grounded perspectives on the impact and policy implications of specific technological developments in computing. ]]> https://insideainews.com/2023/10/02/what-does-the-commercialization-of-generative-ai-mean-for-society/feed/ 0 33544 https://insideainews.com/2023/06/23/book-review-the-kaggle-book-workbook/ https://insideainews.com/2023/06/23/book-review-the-kaggle-book-workbook/#respond Fri, 23 Jun 2023 10:00:00 +0000 https://insidebigdata.com/?p=32621 Kaggle is an incredible resource for all data scientists. I advise my Intro to Data Science students at UCLA to take advantage of Kaggle by first completing the venerable Titanic Getting Started Prediction Challenge, and then moving on to active challenges. Kaggle is a great way to gain valuable experience with data science and machine learning. Now, there are two excellent books to lead you through the Kaggle process. The Kaggle Book by Konrad Banachewicz and Luca Massaron published in 2022, and The Kaggle Workbook by the same authors published in 2023, both from UK-based Packt Publishing, are excellent learning resources. ]]> https://insideainews.com/2023/06/23/book-review-the-kaggle-book-workbook/feed/ 0 32621 https://insideainews.com/2023/04/11/book-review-math-for-deep-learning/ https://insideainews.com/2023/04/11/book-review-math-for-deep-learning/#respond Tue, 11 Apr 2023 13:00:00 +0000 https://insidebigdata.com/?p=32065 One of my favorite learning resources for gaining an understanding for the mathematics behind deep learning is "Math for Deep Learning" by Ronald T. Kneusel from No Starch Press. If you're interested in getting quickly up to speed with how deep learning algorithms work at a basic level, then this is the book for you. ]]> https://insideainews.com/2023/04/11/book-review-math-for-deep-learning/feed/ 0 32065 https://insideainews.com/2023/02/23/book-review-tree-based-methods-for-statistical-learning-in-r/ https://insideainews.com/2023/02/23/book-review-tree-based-methods-for-statistical-learning-in-r/#respond Thu, 23 Feb 2023 14:00:00 +0000 https://insidebigdata.com/?p=30739 Here’s a new title that is a “must have” for any data scientist who uses the R language. It’s a wonderful learning resource for tree-based techniques in statistical learning, one that’s become my go-to text when I find the need to do a deep dive into various ML topic areas for my work. The methods […]]]> https://insideainews.com/2023/02/23/book-review-tree-based-methods-for-statistical-learning-in-r/feed/ 0 30739 https://insideainews.com/2022/03/18/book-review-machine-learning-with-pytorch-and-scikit-learn/ https://insideainews.com/2022/03/18/book-review-machine-learning-with-pytorch-and-scikit-learn/#respond Fri, 18 Mar 2022 13:00:00 +0000 https://insidebigdata.com/?p=28716 The enticing new title courtesy of Packt Publishing, "Machine Learning with PyTorch and Scikit-Learn," by Sebastian Raschka, Yuxi (Hayden) Liu, and Vahid Mirjalili is a welcome addition to any data scientist's list of learning resources. This 2022 tome consists of 741 well-crafted pages designed to provide a comprehensive framework for working in the realm of machine learning and deep learning. The book is brimming with topics that will propel you to a leading-edge understanding of the field. ]]> https://insideainews.com/2022/03/18/book-review-machine-learning-with-pytorch-and-scikit-learn/feed/ 0 28716 https://insideainews.com/2022/01/13/book-review-modern-data-science-with-r-2nd-edition/ https://insideainews.com/2022/01/13/book-review-modern-data-science-with-r-2nd-edition/#respond Thu, 13 Jan 2022 14:00:00 +0000 https://insidebigdata.com/?p=28197 There’s good reason why the word “modern” is in the title of this new title from CRC Press: “Modern Data Science with R, 2nd,” by 3 professors Benjamin S. Baumer, Daniel T. Kaplan, and Nicholas J. Horton – the goal of the text is to provide a solid guide for state-of-the-art data science with the […]]]> https://insideainews.com/2022/01/13/book-review-modern-data-science-with-r-2nd-edition/feed/ 0 28197 https://insideainews.com/2021/12/09/book-review-advanced-r-solutions/ https://insideainews.com/2021/12/09/book-review-advanced-r-solutions/#respond Thu, 09 Dec 2021 14:00:00 +0000 https://insidebigdata.com/?p=27761 Hadley Wickham's popular "Advanced R" book has many intriguing exercises that test your knowledge of deep operations of the R environment. The subject of this book review is a brand new title, "Advanced R Solutions" which is a well-crafted answer book containing all the solutions to each exercise appearing in Advanced R. So many parts of the R language are highlighted in the exercises and solutions, including important topics like: names and values, vectors, subsetting, flow of control, functions, plus large topics like functional programming, object-oriented programming, metaprogramming. Another couple of chapters deal with measuring and improving performance. ]]> https://insideainews.com/2021/12/09/book-review-advanced-r-solutions/feed/ 0 27761