検索キーワード： 数学

お笑い芸人と数学教師の二刀流で活躍中のタカタ先生が算数が「不安」なあなたを算数「ファン」に変えちゃう番組です。 是非お聴きいただき、お子さんへ算数の楽しさを伝えてくださいね！ 質問や感想も随時受付中！ Xにて「 #算数わくわく」でポストしてください。 番組ホームページ　https://rkb.jp/radio/wakuwaku/ タカタ先生X　https://x.com/takatasenseiw

ペンローズが追い求めた「驚きの図形」が見つかった！世界中の数学ファンを熱狂させたペンローズ・タイルの発表（1974年）から半世紀──。

複雑系は、科学が築きあげてきた「近代のパラダイム」を根底から覆した。人間の予想とはかけ離れた、しかし自然のなんらかの真理を表している複雑系が、科学の王道からこぼれ落ちた人々によって発見されていくさまを…

This audiobook is about luck, or more precisely, how we perceive and deal with luck in life and business. It is already a landmark work, and its title has entered our vocabulary. In its second edition, Fooled by Randomness is now a cornerstone for anyone interested in random outcomes.

統計・確率・期待値・平均値など、ビジネスでも使える「算数の基礎」を学び直し。数的思考をアップさせ、数字が読める大人になる！

The aim of this book is to explain, carefully but not technically, the differences between advanced, research-level mathematics and the sort of mathematics we learn at school. The most fundamental differences are philosophical, and listeners of this book will emerge with a clearer understanding of paradoxical-sounding concepts such as infinity, curved space, and imaginary numbers. The first few chapters are about general aspects of mathematical thought.

I’m Logan, Builder for Vex Robotics Team 5156B and during this podcast series I talk about robotics, while actively building my robot!

＜概要＞ 数学は、自然の法則を表現するための美しい言語です。 このポッドキャストでは、数学の基礎から応用まで様々なテーマを取り扱い、数学の魅力をお伝えします。数学が好きな人も、苦手意識を持っている人も、ぜひ数学の魅力に触れてみてください。 ＜初めての方へ＞ 数学沼ラジオのトピックレベルを知りたい場合　→　#1 みんな知ってる数学をさらに深堀りしたい場合　→　#6 日常生活の中でもっと数学を感じたい場合　　　→...

ApplePodcast数学1位。数学ナビゲーターしみに、理系出身文系就職のゆとがナビゲートされちゃう数学ラジオです。たまにゆとが話し手になるゆる物理学ラジオやゆるプログラミングラジオ。だいたい月2,3で配信中！ ネタ自体はヨビノリのたくみさん等が取り扱っているものも多いですが、音声ならではのトークでお届けしています٩( ᐛ )و ▽ 番組へのサポート https://bit.ly/yurusugaku-membership ▽ 公式サイト https://yuru-sugaku.simple.ink/ ▽ お便り https://...

数学が苦手な人も楽しめる数学の話です。podcastとyoutubeで配信しています。 Twitter: https://twitter.com/waku2mathtalk Podcast: https://podcasters.spotify.com/pod/show/wakuwaku-math-talk Youtube: https://www.youtube.com/@math-talk

Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence - and even more so if we hope to participate in the future, rather than being simple bystanders.

待望の数学系Podcast٩( ᐛ )و 人よりちょっと数学を使いこなしてきたゆとと、数学の雑学やクイズを楽しむラジオです。高IQのくせにぜんぜん間違ってたり、いい感じにひらめいたりする思考プロセスをそのままお届けします。 ※番組名を「ゆる数学ラジオ」から「ゆるい数学脳トレラジオ」に変更しております。 ▽友人との2人数学トーク「ゆる数学ラジオ」はこちら ・Spotify https://spoti.fi/3or1hSE ・Apple https://apple.co/35Sgnue ▽その他ゆとが...

We are living through a revolution in machine learning-powered AI that shows no signs of slowing down. This technology is based on relatively simple mathematical ideas, some of which go back centuries, including linear algebra and calculus, the stuff of seventeenth- and eighteenth-century mathematics. It took the birth and advancement of computer science and the kindling of 1990s computer chips designed for video games to ignite the explosion of AI that we see today. In this enlightening book, Anil Ananthaswamy explains the fundamental math behind machine learning.

Math has a reputation for being inaccessible. People think that it requires a special gift or that comprehension is a matter of genes. Yet, the greatest mathematicians throughout history, from Rene Descartes to Alexander Grothendieck, have insisted that this is not the case.

From batting averages and political polls to game shows and medical research, the real-world application of statistics continues to grow by leaps and bounds. How can we catch schools that cheat on standardized tests? How does Netflix know which movies you'll like? What is causing the rising incidence of autism? As best-selling author Charles Wheelan shows us in Naked Statistics, the right data and a few well-chosen statistical tools can help us answer these questions and more.

＼Apple Podcast数学カテゴリで「1位」獲得！／ 東進ハイスクール・山之内聖拡先生＆アシスタントのヒロが、みなさんの勉強の悩みに答えます！聞いてほしい悩みがある人は、次のフォーム、もしくはコメントやTwitterで教えてくださいね！ ●質問フォーム https://forms.gle/dD3oE5tcQ7fmDD4j7

Alan Turing can be regarded as one of the greatest scientists of the 20th century. But who was Turing, and what did he achieve during his tragically short life of 41 years? Best known as the genius who broke Germany's most secret codes during the war of 1939-45, Turing was also the father of the modern computer. Today, all who 'click-to-open' are familiar with the impact of Turing's ideas. Here, B. Jack Copeland provides an account of Turing's life and work, exploring the key elements of his life-story in tandem with his leading ideas and contributions.

Levitt and co-author Stephen J. Dubner show that economics is, at root, the study of incentives: how people get what they want, or need, especially when other people want or need the same thing. In Freakonomics, they explore the hidden side of...well, everything. The inner working of a crack gang...the truth about real-estate agents...the secrets of the Klu Klux Klan. What unites all these stories is a belief that the modern world is even more intriguing than we think. All it takes is a new way of looking, and Freakonomics will redefine the way we view the modern world.

Logic is often perceived as having little to do with the rest of philosophy, and even less to do with real life. In this lively and accessible introduction, Graham Priest shows how wrong this conception is. He explores the philosophical roots of the subject, explaining how modern formal logic deals with issues ranging from the existence of God and the reality of time to paradoxes of probability and decision theory. Along the way, the basics of formal logic are explained in simple, non-technical terms, showing that logic is a powerful and exciting part of modern philosophy.

Under the aegis of machine learning in our data-driven machine age, computers are programming themselves and learning about - and solving - an extraordinary range of problems, from the mundane to the most daunting. Today it is machine learning programs that enable Amazon and Netflix to predict what users will like, Apple to power Siri's ability to understand voices, and Google to pilot cars.