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it is playlist about data science. I'm putting here all podcast in english in related topic. If you know something that should be here please drop me a message with link. And follow me on twitter: @hyzhak_en

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Now that we know about eigenfaces (if you don't, listen to the previous episode), let's talk about how it breaks down. 

Variations that are trivial to humans when identifying faces can really mess up computer-driven facial ID--expressions, lighting, and angle are a few. Something that can easily happen is an algorithm can optimize to identify one of those traits, rather than the underlying trait of whether the person is the same (for example, if the training image is me smiling, you may reject an image of me frowning but accidentally approve an image of another woman smiling). 

Fisherfaces uses a fisher linear discriminant to distinguish based on the dimension in the data that shows the smallest inter-class distance, rather than maximizing the variation overall (we'll unpack this statement), and it is much more robust than our pal eigenfaces when there's shadows, cut-off images, expressions, etc.

http://www.cs.columbia.edu/~belhumeur/journal/fisherface-pami97.pdf

Better Facial Recognition with Fisherfaces

This episode is inspired by one of our projects for Intro to Machine Learning: given a writing sample, can you use machine learning to identify who wrote it? Turns out that the answer is yes, a person’s writing style is as distinctive as their vocal inflection or their gait when they walk. 

By tracing the vocabulary used in a given piece, and comparing the word choices to the word choices in writing samples where we know the author, it can be surprisingly clear who is the more likely author of a given piece of text. 

We’ll use a seminal paper from the 1960’s as our example here, where the Naive Bayes algorithm was used to determine whether Alexander Hamilton or James Madison was the more likely author of a number of anonymous Federalist Papers.

Inferring Authorship (Part 1)

Now that we’re up to speed on the classic author ID problem (who wrote the unsigned Federalist Papers?), we move onto a couple more contemporary examples. 

First, J.K. Rowling was famously outed using computational linguistics (and Twitter) when she wrote a book under the pseudonym Robert Galbraith. 

Second, we’ll talk about a mystery that still endures--who is Satoshi Nakamoto? Satoshi is the mysterious person (or people) behind an extremely lucrative cryptocurrency (aka internet money) called Bitcoin; no one knows who he, she or they are, but we have plenty of writing samples in the form of whitepapers and Bitcoin forum posts. We’ll discuss some attempts to link Satoshi Nakamoto with a cryptocurrency expert and computer scientist named Nick Szabo; the links are tantalizing, but not a smoking gun. “Who is Satoshi” remains an example of attempted author identification where the threads are tangled, the conclusions inconclusive and the stakes high.

Inferring Authorship (Part 2)

The Google AdWords algorithm is (famously) an auction system for allocating a massive amount of online ad space in real time--with that fascinating use case in mind, this episode is part one in a two-part series all about auctions.  We dive into the theory of auctions, and what makes a "good" auction.   

Relevant links:
https://en.wikipedia.org/wiki/English_auction
http://people.ischool.berkeley.edu/~hal/Papers/2006/position.pdf
http://www.benedelman.org/publications/gsp-060801.pdf 

Going Once, Going Twice: Auctions (Part 1)

The Google ads auction is a special kind of auction, one you might not know as well as the famous English auction (which we talked about in the last episode).  But if it's what Google uses to sell billions of dollars of ad space in real time, you know it must be pretty cool.

Relevant links:
https://en.wikipedia.org/wiki/English_auction
http://people.ischool.berkeley.edu/~hal/Papers/2006/position.pdf
http://www.benedelman.org/publications/gsp-060801.pdf 

Sold!  Auctions (Part 2)

This week we are interviewing Anita Tee from Fact Vs Fitness. Anita is a personalized nutritionist, studied her Masters in Personalized Nutrition & her Bachelors in Genetic & Molecular Biology. She is also a personal trainer with the Canadian Register of Exercise & Fitness Professionals.

You can find her at www.factvsfitness.com
Twitter @factvsfitness

You can find Thrival Nutrition at www.thrivalnutrition.com
Facebook - Thrival Nutrition
Twitter - @thrival_orlando
Instagram - thrivalnutrition

Grab your free copy of the Top Ten Superfoods at www.thrivalnutrition.com/superfoods

Episode Seven - Prevention of Metabolic Disorders, Type 2 Diabetes, Heart Disease, and Cancer

Part 3 of "Overcoming Depression" an 8-part series distilling the best advice from thousands of experts into an easy to follow, step-by-step audio program. This section covers Nutrition, Exercise and Sleep routines for taking control of your Depression through Biology.

Overcoming Depression Part 3: Getting a Biological Advantage

What does it take to build a data-driven culture? In this O’Reilly Podcast episode, I pose that question to Ashish Thusoo, founder of Qubole. With his co-founder Joydeep Sen Sarma, Thusoo built a self-service data infrastructure at Facebook beginning in 2007. That infrastructure transformed Facebook’s culture and became part of practically every product decision that the company made.

Building a Data-Driven Culture

In this episode I spoke with Michael Franklin, co-director of UC Berkeley’s AMPLab and chair of the Department of Computer Science at the University of Chicago. AMPLab is well-known in the data community for having originated Apache Spark, Alluxio (formerly Tachyon) and many other open source tools. Today marks the start of a two-day symposium commemorating the end of AMPLab, and we took the opportunity to reflect on its impressive accomplishments.

Building the Next-Generation Big Data Analytics Stack

In this episode of the Super Data Science Podcast, I chat with Chief Data Scientist Damian R Mingle. You will learn about how to build models with 95% accuracy rates, know the 3 top tips on quick wins and winning people over; and get ideas on how to save lives with data science.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/13

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

SDS 013 : 95% Accuracy Models, Winning People Over, and Saving Lives with Damian Mingle

In this episode, I sit down with Brad Knox, founder and CEO of Emoters, a startup building a product called bots_alive—animal-like robots that have a strong illusion of life. We chat about the approach the company is taking, why robots or agents that pass themselves off as human without any transparency should be illegal, and some challenges and applications of reinforcement learning and interactive machine learning.

Brad Knox on Creating a Strong Illusion of Life

In this episode I spoke with Ion Stoica, cofounder and chairman of Databricks. Stoica is also a professor of computer science at UC Berkeley, where he serves as director of the new RISE Lab (the successor to AMPLab). Fresh off the incredible success of AMPLab, RISE seeks to build tools and platforms that enable sophisticated real-time applications on live data, while maintaining strong security. As Stoica points out, users will increasingly expect security guarantees on systems that rely on online machine learning algorithms that make use of personal or proprietary data.

Data is Only as Valuable as the Decisions it Enables

https://www.miamiobgyns.com/blog/how-ph-levels-affect-you/

It seems these days we’re constantly searching for ways to live a well-balanced life. From eating a balanced diet, to finding a healthy work-life balance, to getting the right balance of sleep, good nutrition and exercise, “balance” is today’s hot-trend (that will hopefully have lasting power).

And then of course, there’s the biology of it. The billions of cells in our bodies that must maintain a healthy pH balance in order for our bodies to function at an optimal level.

pH Balance: The ABC’s of Understanding How pH Levels Affect You

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

In this episode of the SuperDataScience Podcast, I chat with Data Science Speaker Daniel Whitenack. You will talk about Pachyderm and know what the company's mission is, discuss about Data Science Workflows and how it's becoming a growing area in data science, learn about the Go Programming Language, and also know the importance of mentorship and the role it plays in both mentees and mentors.

If you enjoyed this episode, check out show notes, resources, and more at http://www.superdatascience.com/61

SDS 061: Discovering Data Science Workflows and The Importance of Mentorship

Do you have dreams in your life which you think it’s time to turn into goals?

If you enjoyed this episode, check out show notes, resources, and more at http://www.superdatascience.com/62

SDS 062: Dreams vs. Goals

In this episode of the SuperDataScience Podcast, I chat with Aspiring Data Scientist Erika Dorland. You will discuss about the different ways to keep up in Data Science, talk about the women in data science community, know the importance of communication skills and you will also get valuable tips on how to leverage your unique strengths when it comes to Data Science whichever background you’re coming from. 

If you enjoyed this episode, check out show notes, resources, and more at http://www.superdatascience.com/63

SDS 063: How to Keep up with Data Science Trends

What's your favorite tool that you have been using in your career and in what way do you think can you improve your skills in using it?

If you enjoyed this episode, check out show notes, resources, and more at http://www.superdatascience.com/64

SDS 064: My Best Tool

In this episode of the SuperDataScience Podcast, I chat with CEO & Co-founder at SFL Scientific Michael Segala. You will discuss about several exciting case studies from the consulting world, see how Data Science can be used in different areas of an organization, learn how it drives real value into business, and finally get valuable insights on data strategy and fantastic tips for those who are building a career in Data Science. 

If you enjoyed this episode, check out show notes, resources, and more at http://www.superdatascience.com/65

SDS 065: How Data Science Brings Value through Consulting Firms

The latest machine learning, A.I., and data career topics from across both academia and industry are brought to you by host Dr. Jon Krohn on the Super Data Science Podcast.

As the quantity of data on our planet doubles every couple of years and with this trend set to continue for decades to come, there's an unprecedented opportunity for you to make a meaningful impact in your lifetime. In conversation with the biggest names in the data science industry, Jon cuts through hype to fuel that professional impact.

Whether you're curious about getting started in a data career or you're a deep technical expert, whether you'd like to understand what A.I. is or you'd like to integrate more data-driven processes into your business, we have inspiring guests and lighthearted conversation for you to enjoy.

We cover tools, techniques, and implementation tricks across data collection, databases, analytics, predictive modeling, visualization, software engineering, real-world applications, commercialization, and entrepreneurship − everything you need to crush it with data science.

SDS 061: Discovering Data Science Workflows and The Importance of Mentorship

Super Data Science: ML & AI Podcast with Jon Krohn