Tag: Algorithmic

Information and Randomness An Algorithmic Perspective


Free Download Information and Randomness: An Algorithmic Perspective by Cristian S. Calude
English | PDF | 2002 | 481 Pages | ISBN : 3540434666 | 37.2 MB
The first edition of the monograph Information and Randomness: An Algorithmic Perspective by Crist ian Calude was published in 1994. In my Foreword I said: "The research in algorithmic information theory is already some 30 years old. However, only the recent years have witnessed a really vigorous growth in this area. . . . The present book by Calude fits very well in our series. Much original research is presented. . . making the approach richer in consequences than the classical one. Remarkably, however, the text is so self-contained and coherent that the book may also serve as a textbook. All proofs are given in the book and, thus, it is not necessary to consult other sources for classroom instruction. " The vigorous growth in the study of algorithmic information theory has continued during the past few years, which is clearly visible in the present second edition. Many new results, examples, exercises and open prob lems have been added. The additions include two entirely new chapters: "Computably Enumerable Random Reals" and "Randomness and Incom pleteness". The really comprehensive new bibliography makes the book very valuable for a researcher. The new results about the characterization of computably enumerable random reals, as well as the fascinating Omega Numbers, should contribute much to the value of the book as a textbook. The author has been directly involved in these results that have appeared in the prestigious journals Nature, New Scientist and Pour la Science.

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Python for Algorithmic Thinking Problem-Solving Skills


Free Download Python for Algorithmic Thinking Problem-Solving Skills
Released: April 26, 2022
Duration: 1h 11m | .MP4 1280×720, 30 fps(r) | AAC, 48000 Hz, 2ch | 175 MB
Level: Advanced | Genre: eLearning | Language: English
The word “algorithm,” at one time the sole province of mathematics and computer science, has entered the modern vernacular because, for better or worse, algorithms have never been more important or more impactful in daily life. If you’re a developer, you need to be familiar with a wide range of algorithmic thinking in order to be able to solve new problems as they present themselves. If you’re already familiar with Python, becoming more versed in algorithmic thinking is a great way to increase your value as a developer. In this course, Robin Andrews explains how Python, because of its clarity and expressiveness, is the ideal tool for exploring algorithmic thinking. He shows you tools to help you understand the flow of algorithms, explains the brute force approach to solving algorithms, details the concepts of time and space complexity with regard to algorithm analysis, the decrease and conquer strategy, and much more.

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