data science

In this episode, I tackle three often conflated terms - AI, machine learning, and deep learning - to shine some light on what exactly they are.

Additional materials: www.superdatascience.com/464

The SuperDataScience Podcast: Machine Learning | AI | Success

SDS 464: A.I. vs Machine Learning vs Deep Learning

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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

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

SDS 047: An Expert Overview of the Deep Learning Models, Supervised and Unsupervised

In this episode of the Data Show, I spoke with Andrew Burt, chief privacy officer at Immuta, and Steven Touw, co-founder and CTO of Immuta. Burt recently co-authored an upcoming white paper on managing risk in machine learning models, and I wanted to sit down with them to discuss some of the proposals they put forward to organizations that are deploying machine learning.

Some high-profile examples of models gone awry have raised awareness among companies for the need for better risk management tools and processes. There is now a growing interest in ethics among data scientists, specifically in tools for monitoring bias in machine learning models. In a previous post, I listed some of the key considerations organization should keep in mind as they move models to production, but the upcoming report co-authored by Burt goes far beyond and recommends lines of defense, including a description of key roles that are needed.

Managing Risk in Machine Learning Models

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Deblina Bhattacharjee joins us to talk about her amazing work in computer vision and give advice for getting into and excelling in the field.

In this episode you will learn:
• Deblina’s master’s program work [4:03]
• Deblina’s computer vision research and Ph.D. [11:46]
• Deblina’s drumming hobby [20:18]
• The daily work [24:40]
• What key skills do you need as a data scientist? [33:21]
• How can a data scientist prepare for the future? [37:03]
• How does Deblina tackle time management? [40:24]

Additional materials: www.superdatascience.com/439

SDS 439: Deep Learning for Machine Vision

This week I answer your questions about machine learning and how to educate yourself further in the field.

Additional materials: www.superdatascience.com/446

SDS 446: Getting Started in Machine Learning

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 464: A.I. vs Machine Learning vs Deep Learning

Super Data Science: ML & AI Podcast with Jon Krohn

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