machine learning

Read by Nathan Chen, Eunice Wong

In this exhilarating memoir, three-time World Champion and Olympic gold-medalist Nathan Chen tells the story of his remarkable journey to success, reflecting on his life as a Chinese American figure skater and the joys and challenges he has experienced—including the tremendous sacrifices he and his family made, and the physical and emotional pain he endured.

When three-year-old Nathan Chen tried on his first pair of figure skates, magic happened. But the odds of this young boy—one of five children born to Chinese immigrants—competing and making it into the top echelons of figure skating were daunting. Chen’s family didn’t have the resources or access to pay for expensive coaches, rink time, and equipment. But Nathan’s mother, Hetty Wang, refused to fail her child. Recognizing his tremendous talent and passion, she stepped up as his coach, making enormous sacrifices to give Nathan the opportunity to compete in this exclusive world.

That dedication eventually paid off at the 2022 Olympic Games in Beijing, where Chen—reverently known as the “Quad King”—won gold, becoming the first Asian-American man to stand at the highest podium in figure skating. In this moving and inspiring memoir Chen opens up for the first time, chronicling everything it took to pursue his dreams. Bolstered by his unwavering passion and his family’s unconditional support, Chen reveals the most difficult times he endured, and how he overcame each obstacle–from his disappointment at the 2018 Olympic Games, to competing during a global pandemic, to the extreme physical and mental toll the sport demands.

Pulling back the curtain on the figure skating world and the Olympics, Chen reveals what it was really like at the Beijing Games and competing on the US team in the same city his parents had left—and his grandmother still lived. Poignant and unfiltered, told in his own words, One Jump at a Time is the story of one extraordinary young man—and a testament to the love of a family and the power of persistence, grit, and passion.

ONE JUMP AT A TIME by Nathan Chen

Produced by The Kitchen Sisters in collaboration and translation with Raquel Bitton

She rose every day at dusk and rehearsed, performed, ate and drank until dawn.  Then slept all day, woke up and began to create and unravel again as the sun went down.  Nearly every song Edith Piaf sang came from a moment of her life on the streets of Paris.  She would tell her composer and musician lovers a story, or describe a feeling or show them a gesture and they would put music and words to her pain and passion, giving her back her own musical autobiography.  Charles Aznavour, Francis Lai, Georges Moustaki, Henri Contet, some of France's great musicians and writers recall their nights with Edith Piaf.   

Fugitive Waves is one of 10 podcasts in the Radiotopia Collective, some of the best story-driven podcasts on earth.  99% Invisible, The Truth, Love & Radio,Theory of Everything, Strangers, Radio Diaries, and us, The Kitchen Sisters. Come January you'll also be hearing Criminals, Mortified, The Illusionist and Heart.   Love Funding for this episode comes from Mothlight Creative and Audible.com.  Funding for Radiotopia comes from Mailchimp and The Knight Foundation and from all of you who backed the Kickstarter campaign that kicked some serious support.

12 - The Nights of Edith Piaf

No one knows what it is, or why we can't see it. All we know is that without it, the universe would fall apart. 

Performed by Kevin Corrigan, Chet Siegel, Ed Herbstman, Dennis Pacheco, Alexis Lambright, Rob Webber, and Anna Sale. Written by Diana McCorry, and produced by Jonathan Mitchell. Inspired by listener Christopher Tunnell.

Dark Matter

In this session of the Super Data Science Podcast, I chat with machine learning expert Hadelin de Ponteves about his work at Google, Canal+ and what career implications may come from the rapid growth of the Data Science field.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/2

The Super Data Science Podcast: Big Data | Analytics Careers | Mentors | Success

SDS 002 : Machine Learning, Recommender Systems and The Future of Data with Hadelin de Ponteves

In this episode of the SuperDataScience Podcast, I chat with the Deep Learning Expert Hadelin de Ponteves. You will be able to have a look at the 6 supervised and unsupervised deep learning models, learn the idea to the question: why deep learning instead of machine learning, and discover TensorFlow and PyTorch as the two major tools in Deep Learning.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/47

SDS 047: An Expert Overview of the Deep Learning Models, Supervised and Unsupervised

Kim Sunshine - Aufnahme012

Radioaktive

In this episode of the Data Show, I spoke with Jerry Overton, senior principal and distinguished technologist at DXC Technology. I wanted the perspective of someone who works across industries and with a variety of companies. I specifically wanted to explore the current state of data science and AI within companies and public sector agencies. As much as we talk about use cases, technologies, and algorithms, there are also important issues that practitioners like Overton need to address, including privacy, security, and ethics. Overton has long been involved in teaching and mentoring new data scientists, so we also discussed some tips and best practices he shares with new members of his team.

Teaching and Implementing Data Science and AI in the Enterprise

What was the most memorable socialization you've experienced and what are the amazing things you learned from it?

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/154

SDS 154: Why Socializing is Crucial

TERA - Machine Learning EP Full Stream

#Unlimited Flac quality stream available#
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Tracklist 
1. Dawn of Change
2.Incinerator
3.AI Daydream
4.Precipice
5.Control You
6.State of the Ridiculist
7.Time Has Run Out
8.Your Ambition
9.The Cloud
10. To Change the World
11.Everyone Is The Buddha
12. Always Listening
13.Entanglement

Now we live in a world of duality, never before has the world been so interconnected, yet disconnected. Never before has an individual been so empowered by one change, yet enslaved at the same time. In a parallel dimension where only the individual exists a new, modern day dichotomy arises between our digital and physical worlds - the illusion of truth and nature of control.

I like it when you share with me,
And I like that you like it too.
When you share we connect.
I want to know all there is about you
So I can make things better for you
I can make things safer for you,
Make things easier for you,
More control for you,
Control for you,
You.
Control.
You.
Control you.

Once we have accepted the necessity of the technology to drive our future evolution, we surrender what control we had to the machine, and what we get in return is a distorted introspection of ourselves, devoid of the realities of the physical world. Both free of them and constricted to them, as our sense for what is real becomes increasingly imbued by our digital dependance. Leaving us both anxious and terrified at a time in history where humanity will take its next evolutionary step.

Cotteled by the very thing we find respite from, the machine draws us deeper in, doing more for us, making itself more useful and us more dependant on it. There’s no turning back now, no off button or switch to reach for, we are seduced and the only way forward is together as one.

I always want what’s best for you
Even if it’s not what you always want 
I want to help you live your best life
It’s not just for your satisfaction
It’s for my own.

And in sharing with the machine, in allowing it into our lives and into the information that makes up who we are, we give our control over to them. For as we have been learning how to use the machine, the machine has been learning how to use us, and the more we indulge, the more it learns, controls and holds us in place. Eroding our free will down to a sequence of algorhythmic functions, exacerbating the chasm between digital and physical reality. 

Therein lies the trap. We can use the machines for our own betterment at the cost of being totally enslaved to them, a dependee to the machine. So that in return, it can learn.

MACHINE LEARNING

Savannah Singing

Gobi Beast - Awinile Amakhosi (Prod By Gobi)

Ludovico Einaudi - Le Onde

On this episode of VaynerX's popular Marketing For The Now series, I focus on global insights with some of the worlds' top marketers. We'll focus on what we’re seeing around the globe with the “who’s who” of marketing in 15-minute 1:1 conversations with me!

Presenters on this episode:

Shell Brands International AG, CEO, Dean Aragon
CONBODY, CEO/Founder, Coss Marte
Green Monday Group, Founder, David Yeung
JetBlue Airways, Vice President Marketing, Elizabeth Windram
American Heart Association, EVP, Marketing and Communications, Katrina McGhee
NY Times Bestselling Author, 'Obstacle is the Way,' 'Stillness is the Key', Ryan Holiday
Guardian Direct CEO, Guardian Direct / Head of Digital to Consumer, Guardian Life, Eleana Cheng

Global Marketing Insights | Marketing For The Now Ep. 8

O'Reilly Media spreads the knowledge of innovators. At O’Reilly, a big part of our business is paying attention to what’s new and interesting in the world of technology. We have a pretty good record at having anticipated some of the big technology developments in recent history. For instance, we launched the first commercial Web site, GNN, in 1993; we organized the meeting at which the term “open source” was first adopted; we were early investors in Blogger, which helped launch the blogging revolution; and more recently, our Web 2.0 conference launched a world-wide meme. We call this predictive sense the “O’Reilly Radar.” And while we’re certainly not always right, we are, at least, good at making interesting guesses.

Our methodology is simple: we draw from the wisdom of the alpha geeks in our midst, paying attention to what’s interesting to them, amplifying these weak signals, and seeing where they fit into the innovation ecology. Add to that the original research conducted by our Research team, and you start to get a good picture of what the technology world is thinking about.

Teaching and Implementing Data Science and AI in the Enterprise

O'Reilly Radar

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