to listen

DataScience

listen while driving

Kullback Leibler divergence, or KL divergence, is a measure of information loss when you try to approximate one distribution with another distribution.  It comes to us originally from information theory, but today underpins other, more machine-learning-focused algorithms like t-SNE.  And boy oh boy can it be tough to explain.  But we're trying our hardest in this episode!

KL Divergence

In this episode of the O’Reilly Media Podcast, I spoke with Gayle Sheppard, vice president and general manager of Saffron AI Group at Intel, and David Thomas, chief analytics officer for Bank of New Zealand (BNZ). Our conversations centered around the utility of artificial intelligence in the financial services industry.

Associative Memory AI: Enabling Machines to Fight Financial Crime With Human-Like Reasoning

The McKinsey Podcast

Artificial intelligence in business: Separating the real from the hype

In this episode of the SuperDataScience Podcast, I chat with the the founders of Cigen, Leigh and Daniel Pullen. You will listen to an overview of RPA or the Robotics Process Automation, talk what it’s all about, how it works, how business gets value from it and also how people can learn this and integrate to their career. You will learn the different RPA tools or the global tools that any business can use across any applications. Also, you will know the concept of Robots-for-Hire and how it is valuable for entrepreneurs.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/173

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

SDS 173: Understanding Robotics Process Automation (RPA) to Disrupt Your Business

When was the last time that you disconnect to technologies?

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/174

SDS 174: A Technology Detox Challenge

In this episode of the SuperDataScience Podcast, I chat with the President and Editor at KDNuggets, Gregory Piatetsky-Shapiro. You will talk about the recent advancements in Data Science, know how Reinforcement Learning can greatly improve the AI capabilities and discuss the noticeable growing trend of automation in the field of data science.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/175

SDS 175: Insights from the Founder of KDnuggets

In this episode of the SuperDataScience Podcast, I chat with the Founder and Chief Technology Officer of CirroLytix Research Services, Dominic Ligot. You will learn the 3 verticals in starting your own analytics business, talk about where the world is going in the space of data analytics and know the demands for analytics from the industries and businesses.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/183

SDS 183: Everything about Data Analytics & its Future

In what situations in your life can you apply the concept of FIFO or LIFO?

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/184

SDS 184: Why You Need Domain Knowledge in Data Science

In this episode of the SuperDataScience Podcast, I chat with the President of McKnight Consulting Group, William McKnight. You will learn about the right pre-requisites in order to have a right analytics organization, know the 4 components of data maturity of an organization, and also find out the 5 different stages of which level an organization can be.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/185

SDS 185: The Pre-Requisites for Analytics to Happen

In this episode of the SuperDataScience Podcast, I chat with the Data Science Mentor, Randy Lao. You will learn how Randy Lao made a big rise in LinkedIn starting out from 45,000 followers and several Data Science jobs in just one year. You will also discuss the whole process of getting a job in Data Science from preparing your portfolio til' getting those data science jobs & opportunities, and get to learn that one thing that Randy is very passionate about which is the "end goal of Data Science".

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/189

SDS 189: How I Got 45,000 Linkedin Followers in One Year

What do you think is your greatest weakness?

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/192

SDS 192: Ace the "Greatest Weakness" Interview Question

In this episode of the SuperDataScience Podcast, I chat with the Artificial Intelligence expert, Roman Yampolskiy. You will discuss on Artificial Intelligence safety, talk about how AI is going to quickly take over in the coming years and why we have to prioritize AI safety for safer machines, and also get valuable advices on how to start a career in AI, for business owners, and for professionals on how to get to high-end jobs.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/193

SDS 193: A serious talk on AI taking over jobs

In this episode of the SuperDataScience Podcast, I chat with the Epic Life Coach, Carl Massy. This episode is a total pause from the Data Science world as talks about the secret to happiness. You will know what led Carl to follow his passion in helping people find inner happiness, learn how to establish daily rituals to have a solid foundation, and get the 3 valuable tips on how to change your state of mind.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/197

SDS 197: How to be Happy and Successful

In this episode of the SuperDataScience Podcast, I chat with Associate Professor at NYU Stern School of Business, Kristen Sosulski. You will talk about Kristen's experience in visualizing data, how she learned to communicate findings, present data visualization insights and how she has helped people on how to read data, charts and graphs. You will also learn why Data Visualization is an entry pathway into Data Science and get to know the top tips that Kristen has been practicing in order to be successful in this field.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/199

SDS 199: Data Visualization Insights from NYU

Convex optimization is one of the keys to data science, both because some problems straight-up call for optimization solutions and because popular algorithms like a gradient descent solution to ordinary least squares are supported by optimization techniques. But there are all kinds of subtleties, starting with convex and non-convex functions, why gradient descent is really an optimization problem, and what that means for your average data scientist or statistician.

Convex (and non-convex) Optimization

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 173: Understanding Robotics Process Automation (RPA) to Disrupt Your Business

Super Data Science: ML & AI Podcast with Jon Krohn