The Banana Data Podcast

Ethical Implications of Humanizing Your Data

Floor to Ceiling Data Strategy

Data Visualization w/ Nathan Mannheimer, Director of Data Science & ML at Tableau

Leverage Storytelling With Data

The Importance of Human in the Loop AI With Christina Hsiao

What Happens When Humanization Fails? A Conversation With Jeremie Harris of Towards Data Science

Methodology & Functionality in Differing Data Science Roles

Rise of the Data Citizen

Create Technological Emotional Bonds w/ Creative Intelligence

What Does It Mean to Humanize Your Data?

In English Please: Part 2

In English Please: Part 1

Banana Byte: AI Is Revolutionizing Biological Sciences - What Are the Implications?

2021 Trends in AI

Banana Byte: Data Tools We're Thankful For

What Does It Mean to Be a Data Scientist?

Banana Byte: Using AI to extend People Analytics

How The COVID Monitor Project is Driving Data Transparency & Access

Our Social Network

Banana Byte: Is Investing Your Time in Code Worth It?

The Data Debate Stage

Banana Byte: The Good, the Bot, the Ugly

A Deeper Look at CAPTCHA Systems

Banana Byte: Misinterpreted Data and Understanding Uncertainty

Conscious Data Disclosure & AI Consumption

Banana Byte: Viral Tweets, Skynet, and The Reality of Data Science

Exciting Global AI

Banana Byte: How Much Math Do You Need for Data Science?

Machine Learning Pet Peeves

Weighing the Good and Bad in AI

Banana Byte: Understanding the Value of Deep Learning

Banana Byte: The Hidden Costs of Cloud Computing

Banana Byte: Zoom Privacy

Data Nuance & Human-in-the-Loop Monitoring

Fighting Cheating AI & Redefining AI companies

The Messiness of Data

Analytics in the NFL & Revolutions in Data Discovery

Deepfakes & Data Upskilling

Is AI Worth it?

The Roles in Data Science, feat. Tristan Handy, CEO & Founder of Fishtown Analytics

How We Talk about AI, feat. Karen Hao, MIT Technology Review

The Everyday of AI

The Future (and the now) of AI with Azalia Mirhoseini, Senior Researcher at Google Brain

Do I do AI?

Finding Community in Data Science with Reshama Shaikh, key scikit-Learn sprint organizer

Why Open Source? feat. Andreas Mueller, a Core Contributor of scikit-Learn

Predicting AI Trends for 2020

Life after Production, a Tale of Technical Debt with Dan Shiebler, Twitter Eng

The Essentials (and not-so essentials) of Data Science Pipelines

What Makes a Good Data Science Practice

The Death of Data Viz, Cross-Cultural AI, and AI Auditing

Prioritizing training data, model interpretability, and dodging an AI Winter

Building accessible queries, codes, and speech using AI

AI Meets World: GDPR, the AI Job Apocalypse, and AI’s carbon footprint

A New Kind of Relationship with AI: Robopets, AI Art, and AI EQ

The future of data according to predictions, Python 3.0, and people.

Culpability in AI failures, Fooling NNs with NNs, AI for cancer screenings, and Epsilon Greedy Multi-Armed Bandits

Biased Data & the Perfect Answer, Multi-Armed Bandits, and the GPUs Behind Your Neural Networks

Being an Ethical Data Scientist, Federated Learning in Healthcare, and Dropping the “Best Model” Approach