Superdatascience

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

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

In this episode of the SuperDataScience Podcast, I chat with the legend of visual journalism, Alberto Cairo, who talks about understanding if your data is measuring the right thing that you want to be measuring. You will hear about Simpson's paradox and the ecological fallacy. You will learn about the four kinds of literacy, exploratory data analysis versus communicating results, and how to create a narrative structure in your visualization and convey the insights in a certain way so that people can better understand them. And finally, you will hear about ethics in data visualization. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/271

How can you leverage this to help you focus on your work in data science? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/270

In this episode of the SuperDataScience Podcast, I chat with Justin Fortier, the principal data scientist at ViralGains. You will hear about ad tech, performing insights, getting insights, and making decisions within milliseconds with data science. You will learn about the business impact, why business impact is ultra-important, and on the other hand, why user experience is an ultra-important factor for a data scientist to consider more and more in today's world. You'll also learn about Justin's path from managing data scientists at large organizations, to being the single data scientist at smaller startups and you will hear some very interesting decisions he made throughout his career. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/269

How can you see data science disrupting and progressing the insurance industry in the future? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/268

In this episode of the SuperDataScience Podcast, I chat with Manasi Vartak, founder and CEO at Verta.ai. You will learn about model tracking, versioning, and maintenance. You will also learn what data maturity means and what are the 3 areas where top-tier data science teams are investing in. You will hear a great discussion about the boom that will happen with machine learning in the next 3 years and what you can do to prepare your career or your business for the future. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/267

Where are you overexploiting patterns in your life and where can you be more open to some exploration? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/266

In this episode of the SuperDataScience Podcast, I chat with Frank Kane, an expert and top instructor in the field of big data, who also worked in Amazon for 10 years. You will learn how data science and big data have been different but are now converging into something that is very intertwined. You will hear about recommender systems such as user-based and item-based collaborative filtering as well as other types of recommender systems and where this space of recommender systems is going. You will also hear about singular value decomposition or SVD model-based methods, deep learning and Amazon DSSTNE. And in the end, you will learn some very valuable tips on how to get hired by big companies like Amazon. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/265

How do you see data science continuing to improve the world’s most important industry? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/264

In this episode of the SuperDataScience Podcast, I chat with Eoin Murray, the founder of Kyso.io, a platform where you can blog about your data science projects using tools such as Jupyter notebooks. You will learn what the platform means for data scientists and how you can use it to build your online presence and online portfolio. You will hear about startups and how you can jump into creating a startup, what accelerators are, what angel investors are, and what venture capital funds are. Yu will also hear where data science is going and whether or not data science should be a certified profession. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/263

How can you put a routine on a goal you’re trying to achieve? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/262

In this episode of the SuperDataScience Podcast, I chat with Andrei Lyskov, a data science writer, who shares not only his experience but also his research and his thoughts and ideas in the space of getting a job in data science. You will learn about the trichotomy of control and the stages involved in job interviews in data science. You will also learn about the importance of referrals and portfolio, and you will hear about learning how to learn. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/261

How can we, as data scientists, scale the existing technologies in real estate? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/260

In this episode of the SuperDataScience Podcast, I chat with Stephen Welch, a computer vision and neural networks expert who will share a ton of information about the space of self-driving cars. You will learn about self-driving cars starting from the history of neural networks and how that was associated with self-driving cars from the '60s, '70s, '80s and all the way until now. You'll also learn about autonomous driving and the three components in the neural networks related to autonomous driving and what they are and how they work. You will find out about the five different levels of autonomous driving and what to expect in the next 10-20 years. You will hear a case study of how machine learning can be applied to historically older industries and you will also hear some very valuable career advice. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/259

How can you work S.L.O.W.L.Y. into your daily routine? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/258

In this episode of the SuperDataScience Podcast, I chat with Melanie Mitchell, one of the leading researchers in the field of AI. You will learn about complexity, what it is and how it works, and how it can be seen in different areas of life. You will hear about common sense, meta-cognition, explainable AI, and you will also hear Melanie's ideas and thoughts on the future of AI, which break down into two areas which you'll find out in this podcast. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/257

How do you see data science assisting in the transportation industry in the future? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/256

In this episode of the SuperDataScience Podcast, I chat with the founder of PyImageSearch.com, Adrian Rosebrock, who gives us a great overview of the space of computer vision. You will learn what computer vision was in the past, what it is now, and most importantly, what it will be in the future and what you need to prepare for if you're interested in computer vision. You will also learn about OpenCV and how to quickly get started with it as it is one of the most popular libraries and tools for computer vision in the world right now. If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/255

What negative and positive emotions do you find most often acknowledging in yourself? If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/254