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DataScience

In this episode of the SuperDataScience Podcast, I chat with Aspiring Data Scientist Nicholas Cepeda. You will be able to discover the many different pathways in Data Science, learn R from a SQL background and know about SAS Enterprise Miner. 

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/41

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

SDS 041: An Inspiring Journey from a Totally Different Background to Data Science

In this episode of the SuperDataScience Podcast, I chat with the unstoppable, Rico Meinl. You will learn the practical applications of AI and why is it important, know the different tactics on how to apply your passion while still learning, and listen to a discussion on how to setup an AI lab at an e-commerce ready company.

If you enjoyed this episode, check out show notes, resources, and more at https://www.superdatascience.com/123

SDS 123: How to be Unstoppable: Data Science, Reckless Commitment & Artificial Intelligence

In this episode of the SuperDataScience Podcast, I chat with the aspiring data scientist, Mike Taveirne. You will discuss the five stages of data science process for starters, get valuable tips for people who want to learn and transition to data science, and know how to apply your data science knowledge to your hobbies and interests.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/159

SDS 159: From Developer to Data Scientist

In this episode of the SuperDataScience Podcast, I chat with Associate Professor at the University of California San Diego, Bradley Voytek, who was the first data scientist, and the person to kickstart data science at Uber. You will hear a lot about his past work in Uber and his current work in UCSD. You will learn four very valuable philosophical points about data science being a separate field and you will also learn what data science skills can help you resist automation.

If you enjoyed this episode, check out show notes, resources, and more at www.superdatascience.com/253

SDS 253: Solving Problems With Data Science & Uber

There’s been a lot of interest lately in the attention mechanism in neural nets—it’s got a colloquial name (who’s not familiar with the idea of “attention”?) but it’s more like a technical trick that’s been pivotal to some recent advances in computer vision and especially word embeddings. It’s an interesting example of trying out human-cognitive-ish ideas (like focusing consideration more on some inputs than others) in neural nets, and one of the more high-profile recent successes in playing around with neural net architectures for fun and profit.

Attention in Neural Nets

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

The topic of bias in word embeddings gets yet another pass this week. It all started a few years ago, when an analogy task performed on Word2Vec embeddings showed some indications of gender bias around professions (as well as other forms of social bias getting reproduced in the algorithm’s embeddings). We covered the topic again a while later, covering methods for de-biasing embeddings to counteract this effect. And now we’re back, with a second pass on the original Word2Vec analogy task, but where the researchers deconstructed the “rules” of the analogies themselves and came to an interesting discovery: the bias seems to be, at least in part, an artifact of the analogy construction method. Intrigued? So were we…

Relevant link:
https://arxiv.org/abs/1905.09866

Revisiting Biased Word Embeddings

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

Sinan Ozdemir is back again, this time talking about his work since his company Kylie.ai was acquired by Directly. We discuss his work, the way he is creating human and AI synergy and the future of NLP as it continues to progress.

In this episode you will learn:
• Sinan’s company acquired [7:29]
• Explainable deep learning models [16:13]
• Airbnb case study [19:42]
• Microsoft case study [22:25]
• Sinan’s role at Directly [25:57]
• Work with Sinan [32:57]
• Preview of Sinan at DSGO [38:38]
• BERT [43:18]
• Sinan’s prediction for NLP in 2020 [53:17]

Additional materials: www.superdatascience.com/333

SDS 333: BERT and NLP in 2020 and Beyond

Stratos Hadjioannou is a freshly hired data scientist who is self-taught and made the jump to visit DSGO. He talks about his learnings, putting himself in a data science ecosystem, and how to tackle interviews with little experience.

In this episode you will learn: 
• Where did Stratos start? [6:16]
• How to keep the momentum for learning [12:20]
• Stratos’s goals [19:35]
• Planning the steps to getting a data science job [23:01]
• Triad for successful interviews [32:47]
• Application process [34:53]
• Experiences from the first data science job [45:51]

Additional materials: www.superdatascience.com/351

SDS 351: Self-Starting In Data Science

DJ Patil talks about ethics in data science and the importance of data science communities working together to make sure data science is an accelerant of solutions for our children and our children’s children.

In this episode you will learn:
• How does it feel to be the person who created data science as we know it now? [3:17]
• What data science is not [6:01]
• Ethics and data science development in different countries [10:00]
• What is the “biorevolution”? [16:02]
• The importance of data sharing [20:10]
• The current state of Chief Data Scientist of USA [24:07]
• LinkedIn Q&A [26:03]
• What to think about when you think about data science [44:08]

Additional materials: www.superdatascience.com/355

SDS 355: DJ Patil on Harnessing the Power of Data Science Community

In this episode, I talk about an issue I’ve been having when it comes to phasing my mind out of work and into post-work activities, a concept called “attention residue”.

Additional materials: www.superdatascience.com/374

SDS 374: Remember to Wind Down

Greg Pavlik joins me for a great talk about the current state of the cloud and how single practitioners and small businesses can take advantage of cloud services.

In this episode you will learn:
• Will we have cloud-based solutions for VR and working from home? [8:15]
• Greg’s career journey [11:50]
• From Hadoop to Cloud [23:35]
• The cloud element in data science [30:17]
• Data science and AI in Oracle [33:00]
• Is Oracle more suited for larger companies only? [37:35]
• Fundamental differences between Oracle Cloud, Amazon, and Azure [42:12]
• Trends in data science and data management [45:14]
• Why should someone choose Oracle over any other open source? [52:50]
• How does the future of data management look like? [56:00]
• 5G and edge computing [1:01:36] 
• Greg’s recommendation to data scientists [1:04:28]

Additional materials: www.superdatascience.com/375

SDS 375: Utilizing Oracle Cloud as an Enterprise, Small Business, or Developer

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 253: Solving Problems With Data Science & Uber

Super Data Science: ML & AI Podcast with Jon Krohn