Showing titles in Mathematics

Les algorithmes nous entourent, ils sont partout. On les trouve dans nos smartphones, dans nos ordis, dans la cuisine, et même dans nos chambres à coucher. Les plus connus s’appellent Google, Siri, Alexa, et ils apprennent de nous et de nos données. Avec Ex Machina, les chercheuses et les chercheurs de l’Université Paris Dauphine–PSL nous emmènent dans leurs réflexions pour mieux comprendre l’intelligence artificielle et ce que son arrivée dans notre quotidien implique pour nous, les humains. Le podcast Ex Machina aborde l’impact des intelligences artificielles et des ...

Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions which will be addressed in the podcast series Learning Machines 101.

UN PODCAST PARA EL CAFÉ es un segmento de tertulia que busca hablar de temas importantes que no encajan en una entrevista y son de tipo filosófico, cultural, del diario vivir y repercute de alguna u otra forma en nuestras vidas. Un emprendimiento de Radio Futuro Internacional.

Dare senso al mondo, alle esperienze quotidiane e, ancor più, agli eventi che ci sorprendono o dai quali può dipendere la nostra sopravvivenza. Quante volte una dimenticanza o un impercettibile ritardo nel compiere un'azione hanno conseguenze importanti o addirittura drammatiche? È ciò che i matematici chiamano caos, un concetto che ha un'origine assai remota nel pensiero umano, condizione della bellezza della natura per i filosofi presocratici, forza speculare all'armonia nel taoismo.

The complexity of mathematics - its abstract rules and obscure symbols - can seem very distant from the everyday. There are those things that are real and present, it is supposed, and then there are mathematical concepts: creations of our mind, mysterious tools for those unengaged with the world. Yet, from its most remote history and deepest purpose, mathematics has served not just as a way to understand and order, but also as a foundation for the reality it describes.

Do your kids hate math? Many students fail to understand the value of math, and some grow to hate it. Want proof? Read genuine letters students wrote to math, compiled by the authors in this Dear Math book. Discover the root of this problem. 15-year veteran math teacher, Sarah Strong, and her high school student, Gigi Butterfield, address concerns about negativity around teaching and learning math and why kids hate math (at least some of them). Digging into the feelings math evoked in hundreds of middle and high school students—that math is unnecessary, oppressive, and intimidating—the ...

From sonnets to fairytales to experimental French literature, Once Upon a Prime takes us on an unforgettable journey through the books we thought we knew, revealing new layers of beauty and wonder. Professor Hart shows how maths and literature are complementary parts of the same quest, to understand human life and our place in the universe.

La plupart des gens aiment les maths. L'ennui, c'est qu'ils ne le savent pas. Dans les temps préhistoriques, les maths sont nées pour être utiles. Les nombres servaient à compter les moutons d'un troupeau. La géométrie permettait de mesurer les champs et de tracer des routes. L'histoire aurait pu en rester là, mais au fil des siècles, les Homo sapiens furent bien étonnés de découvrir les chemins sinueux de cette science parfois abstraite.

You may have watched hundreds of episodes of The Simpsons (and its sister show Futurama) without ever realising that they contain enough maths to form an entire university course. In The Simpsons and Their Mathematical Secrets, Simon Singh explains how the brilliant writers, some of the mathematicians, have smuggled in mathematical jokes throughout the cartoon’s 25-year history, exploring everything from p to Mersenne primes, from Euler’s equation to the unsolved riddle of P vs. NP, from perfect numbers to narcissistic numbers and much more.

If you are convinced that the world today is producing more data than the previous decades, then you understand that processing yesterday's data for today's use at times is not enough. The level of data analysis that is needed in highly competitive business environment needs to be processed, analyzed, and used immediately for businesses to be ahead of their competition. Having this in mind, you need to understand from the ground up, what data is, the different types of data and how you should identify the right data for your business. To help you understand the simple basics of data and how it needs to be analyzed, then Data Analytics for Beginners is the book that you have been waiting for.

Oliver Johnson reveals how mathematical thinking can help us understand the myriad data all around us. From the exponential growth of viruses to social media filter-bubbles; from share-price fluctuations to growth of computing power; from the datafication of our sports pages to quantifying climate change. Not to mention the things much closer to home: ever wondered when the best time is to leave a party? What are the chances of rain ruining your barbecue this weekend? How about which queue is the best to join in the supermarket?

What if there was an investment opportunity which could triple your money in just three months? A second cryptocurrency boom is coming and one that will make last December’s gains look small. This time, institutional money is coming from Wall Street, and when banks and hedge funds get involved, prices rise faster than ever before. Needless to say, millionaires will be made. Rat races will end. Lives will be changed forever. The question is will yours be one of them?

Bettor Thinking isn’t just another sports betting podcast—it’s your masterclass in decision-making excellence. Join host John ”Statsational” Alesia as he explores the fascinating intersection of sports betting, behavioral psychology, and analytical thinking through conversations with an elite roster of guests including Wall Street quants, professional bettors, behavioral economists, and industry innovators. Each episode delivers actionable insights that go beyond basic betting advice, diving deep into the mental models, analytical frameworks, and decision-making processes that ...

Covering topics and innovations in biomedical informatics, healthcare, medicine, science, engineering, and artificial intelligence (with the occasional musical surprise)

Hosted by Gabriel Hesch and Autumn Phaneuf, who have advanced degrees in electrical engineering and industrial engineering/operations research respectively, come together to discuss mathematics as a pure field all in its own as well as how it describes the language of science, engineering, and even creativity. Breaking Math brings you the absolute best in interdisciplinary science discussions - bringing together experts in varying fields including artificial intelligence, neuroscience, evolutionary biology, physics, chemistry and materials-science, and more - to discuss where humanity is...

Un estimulante viaje que comienza con la aparición de los números primos—objeto de profundas y sorprendentes investigaciones matemáticas a lo largo de los siglos—y nos lleva hasta los límites del infinito, el número más grande de todos y el único que consigue que las matemáticas y la filosofía encuentren un lugar común.

In this podcast, we describe and advocate for the student-centered teaching philosophy developed and practiced by Jack Albers over 50+ years of teaching mathematics.

Math! Science! History! is a podcast about the history of people, theories, and discoveries that have moved our scientific progress forward and spurred us on to unimaginable discoveries. Join Gabrielle Birchak for a little math, a little science, and a little history. All in a little bit of time.

in Mandarin/zh, with EfficientNet, with pretrained weights, freeze all the weights, then you can add your top, then fit/train, you can reach satisfied accuracy with very limited training time/epochs; then unfreeze the layers -20: of non BN layers, change its trainable to True, then fit, you can get even better accuracy with very few like 10 epochs. So this is called transfer learning.

Welcome to the Brain Training Podcast, the daily audio workout for your head. In this podcast we have two games for you, each with three rounds which get progressively harder. To enjoy the full experience, relax, and avoid distractions whilst you listen. Hosted on Acast. See acast.com/privacy for more information.