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DataScience

The artificial intelligence field is normally seen as burgeoning and new, populated with lots of small, scrappy companies aiming to become the next de-facto solution, with maybe one exception - “Big Blue”. IBM has been involved since the ‘beginning’ and is perhaps best known for Watson, which has from Jeopardy to a range of applications in small and big businesses, as well as the public sector. Swami Chandrasekaran is chief technologist of industry apps and solutions for IBM, and he speaks in this episode about what he sees as some of the low-hanging fruit for applying predictive models to business data. Swami has seen this technology applied in a variety of contexts, from automotive and shipping to telcos and more, providing an informed perspective for industry executives, data scientists, and anyone else interested in the intersection of predictive analytics and business.

Predictive Analytics Offers Customized Solutions to Complex Problems

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

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

SDS 185: The Pre-Requisites for Analytics to Happen

Fernando Machado is a marketer on the up. Since joining Burger King in 2014 after 18 years at Unilever he has been celebrated for the brand’s quirky creativity and its willingness to take a stand on societal issues, achieved on limited budget. He was recently named 'Grand Brand Genius of the Year' by Ad Week in the US, an award that followed Burger King being crowned Creative Marketer of the Year at Cannes in 2017.

In this wide-ranging interview, Machado discusses:
·        Why the “great idea” is everything in marketing
·        The importance of having a challenger mindset
·        Why data-led companies don’t need marketers
·        His quest to convince people that fast-food is “not evil”   
·        Why Burger King’s brand DNA justifies its purpose driven campaigns

Marketing Week Meets: Fernando Machado

In this episode of the SuperDataScience Podcast, I chat with the Data Science Headhunter and Head of Analytics Recruitment at IT Search and Selection, Adrian Clarke. You will learn about the state of the data science industry globally and the different data science roles that exist in the world. You will also learn what to expect in terms of data science salaries and why there is a huge demand for data scientists. You will hear about the concept of hybrid professional and a lot of valuable career insights.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/239

SDS 239: From Candidate to Career: Pathways for Data Scientists

How would you approach to adopting AI into your business?

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/240

SDS 240: State of Artificial Intelligence in Business

How can you use data science to help keep the energy industry helpful and ethical towards the planet and future generations?

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/272

SDS 272: Data Science in Energy

In this episode of the SuperDataScience Podcast, I chat with Matthew Rosenquist, one of the top leading world experts in the space of cybersecurity. You will learn what balance in cybersecurity means and what the dark web is. You will hear how Matthew's career developed and how he thinks about the strategy of cybersecurity. You will also learn about the valuable role of data science in cybersecurity and the steps you can take to get into this space.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/273

SDS 273: Predict, Prevent, Detect: Cyber Security

What has happened to you recently that could call for clarity from a mentor or coach?

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/274

SDS 274: Ask the Right Question

In this episode of the SuperDataScience Podcast, I chat with the Machine Learning Research Scientist, John Langford. You will hear about unsupervised, supervised learning and reinforcement learning, and the differences between the three. You will learn about applications of contextual bandits and reinforcement learning in general, YOLO style algorithms versus simulator algorithms, technics for avoiding local optimums. You will also learn about the balance between exploration and exploitation, learning to search and active learning.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/275

SDS 275: Machine Learning Through Reinforcement & Contextual Bandits

How can you use these processes in your industry? 

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/276

SDS 276: Data Science in Wealth Management

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 239: From Candidate to Career: Pathways for Data Scientists

Super Data Science: ML & AI Podcast with Jon Krohn