From 9cb599bcfb768cbdc4b06194cec98dc3a2a687cc Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Stjepan=20Jurekovi=C4=87?= Date: Thu, 19 Aug 2021 20:43:39 +0200 Subject: [PATCH 1/2] Added A&DS for Massive Datasets Hi, Stjepan from Manning here. I thought this title might be a good match to your list. Thank you for considering it. Best, --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 55a9178..a0ff451 100644 --- a/README.md +++ b/README.md @@ -136,6 +136,7 @@ Share the list with your classmates, your friends and everyone :) | ★★★ | [Algorithms](https://www.amazon.com/Algorithms-4th-Robert-Sedgewick/dp/032157351X), by Robert Sedgewick and Kevin Wayne | This book is neatly categorized, coupled with elaborate explanations and fantastic illustrations. It is used in some IOI training camps as a textbook. | | | [Algorithms and Data Structures in Action](https://www.manning.com/books/algorithms-and-data-structures-in-action), by Marcello La Rocca | This book provides a different approach to algorithms, balancing theory with a more practical angle, with a section per-chapter focusing on how to apply algorithms to real-world use cases that can be found in your daily work, or in competitive programming; it also presents a blend of classic, advanced, and new algorithms. | | ★★★ | [Algorithms](https://jeffe.cs.illinois.edu/teaching/algorithms/), by Jeff Erickson | A free electronic version of a self-published textbook licensed under CC by 4.0. This is a well written book from lecture notes of theoretical computer science courses at the University of Illinois. Covers the main paradigms of backtracking, dynamic programming, greedy, and particularly graphs in depth. | +| ★★★ | [Algorithms and Data Structures for Massive Datasets](https://www.manning.com/books/algorithms-and-data-structures-for-massive-datasets), by Dzejla Medjedovic, Emin Tahirovic, and Ines Dedovic | Algorithms and Data Structures for Massive Datasets teaches you to take advantage of data processing and analytics techniques specifically designed for large distributed datasets. | ### Books for Mathematics From ede98d3f9499d1003e897729315d41d689fbf559 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Stjepan=20Jurekovi=C4=87?= Date: Tue, 23 Nov 2021 14:25:31 +0100 Subject: [PATCH 2/2] Added two new titles to Books Hi, Stjepan from Manning here. I thought these two titles - Graph Algorithms for Data Science & Math for Programmers - might be a good match for your list. Thank you for considering it. Best, --- README.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/README.md b/README.md index a0ff451..4f580bb 100644 --- a/README.md +++ b/README.md @@ -137,6 +137,7 @@ Share the list with your classmates, your friends and everyone :) | | [Algorithms and Data Structures in Action](https://www.manning.com/books/algorithms-and-data-structures-in-action), by Marcello La Rocca | This book provides a different approach to algorithms, balancing theory with a more practical angle, with a section per-chapter focusing on how to apply algorithms to real-world use cases that can be found in your daily work, or in competitive programming; it also presents a blend of classic, advanced, and new algorithms. | | ★★★ | [Algorithms](https://jeffe.cs.illinois.edu/teaching/algorithms/), by Jeff Erickson | A free electronic version of a self-published textbook licensed under CC by 4.0. This is a well written book from lecture notes of theoretical computer science courses at the University of Illinois. Covers the main paradigms of backtracking, dynamic programming, greedy, and particularly graphs in depth. | | ★★★ | [Algorithms and Data Structures for Massive Datasets](https://www.manning.com/books/algorithms-and-data-structures-for-massive-datasets), by Dzejla Medjedovic, Emin Tahirovic, and Ines Dedovic | Algorithms and Data Structures for Massive Datasets teaches you to take advantage of data processing and analytics techniques specifically designed for large distributed datasets. | +| ★★★ | [Graph Algorithms for Data Science](https://www.manning.com/books/graph-algorithms-for-data-science), by Tomaz Bratanic | This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. | ### Books for Mathematics @@ -148,6 +149,7 @@ Share the list with your classmates, your friends and everyone :) | ★★☆ | [Introduction to Probability](http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/book.html), by Charles M. Grinstead, J. Laurie Snell | This is a well-written introductory probabilities book. ... It's free for [download (pdf)](http://www.dartmouth.edu/~chance/teaching_aids/books_articles/probability_book/amsbook.mac.pdf) (released under GNU Free Documentation License). | | ★★☆ | [How to Solve It: A New Aspect of Mathematical Method](https://www.amazon.com/How-Solve-It-Mathematical-Princeton/dp/069111966X), by G. Polya | An old-time classic. In this book, the author provides a systematic way to solve problems creatively. | | ★★☆ | [Intermediate Counting & Probability](https://artofproblemsolving.com/store/item/intermediate-counting), by David Patrick | Topics in counting and probability byformer USA Mathematical Olympiad winner David Patrick , topics include inclusion-exclusion, 1-1 correspondences, the Pigeonhole Principle, constructive expectation, Fibonacci and Catalan numbers, recursion, conditional probability, generating functions, graph theory, and much more.. | +| ★★☆ | [Math for Programmers](https://www.manning.com/books/math-for-programmers), by Paul Orland | Math for Programmers teaches the math you need to achieve a career in data science, machine learning, computer graphics, and cryptography, concentrating on what you need to know as a developer. | ## Sites for Practice