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40 Algorithms Every Programmer Should Know

(ebook) (audiobook) (audiobook) Język publikacji: angielski
Autor:
Imran Ahmad
40 Algorithms Every Programmer Should Know Imran Ahmad - okładka książki

40 Algorithms Every Programmer Should Know Imran Ahmad - okładka książki

40 Algorithms Every Programmer Should Know Imran Ahmad - okładka audiobooka MP3

40 Algorithms Every Programmer Should Know Imran Ahmad - okładka audiobooks CD

Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
382
3w1 w pakiecie:
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Ebook

129,00 zł

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Algorithms have always played an important role in both the science and practice of computing. Beyond traditional computing, the ability to use algorithms to solve real-world problems is an important skill that any developer or programmer must have. This book will help you not only to develop the skills to select and use an algorithm to solve real-world problems but also to understand how it works.

You'll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, such as searching and sorting, with the help of practical examples. As you advance to a more complex set of algorithms, you'll learn about linear programming, page ranking, and graphs, and even work with machine learning algorithms, understanding the math and logic behind them. Further on, case studies such as weather prediction, tweet clustering, and movie recommendation engines will show you how to apply these algorithms optimally. Finally, you'll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks.

By the end of this book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.

O autorze książki

1 Imran Ahmad

Imran Ahmad jest certyfikowanym instruktorem Google z wieloletnim doświadczeniem. Wykłada Pythona, uczenie maszynowe i głębokie, algorytmikę oraz zagadnienia big data. Przez ostatnie lata pracował w rządowym laboratorium Kanady nad projektem z zakresu uczenia maszynowego. Obecnie zajmuje się algorytmami używającymi GPU do optymalnego trenowania złożonych modeli uczenia maszynowego.

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