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Adventures in Machine Learning

Charles M Wood
Machine Learning
Data Science
Generative AI
Project Scoping
Collaboration
Python
Success Criteria
AI Skills
Job Descriptions
SQL
Artificial Intelligence
Data Engineering
Software Development
Closed Source Models
Open Source Models
Mlflow
Spark
Databricks
Data ML Infrastructure
API Design

Machine Learning is growing in leaps and bounds both in capability and adoption. Listen to our experts discuss the ideas and fundamentals needed to succeed as a Machine Learning Engineer.Become a supporter of this podcast: www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.

PublishesWeeklyEpisodes209Founded5 years ago
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How ToEducationTechnology

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Artwork for Adventures in Machine Learning

Latest Episodes

In this episode, we dive deep into the evolving landscape of digital marketing and brand storytelling. We explore how the intersection of authenticity, community, and technology is reshaping how brands connect with people—and why it's no longer just ... more

Welcome back to another episode of Adventures in Machine Learning, where hosts Michael Berk and Ben Wilson delve into the intricate process of implementing model serving solutions. In this episode, they explore a detailed case study focused on enhanc... more

Welcome to another insightful episode of Top End Devs, where we delve into the fascinating world of machine learning and data science. In this episode, host Charles Max Wood is joined by special guest Pierpaolo Hipolito, a data scientist at the SAS I... more

What do cows and camels have to do with the human brain? The latest developments in machine learning, of course! In this episode, Michael and Ben dive into a new white paper from Facebook AI researchers that reveals a LOT about the future of modeling... more

Key Facts

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Contact Information
Podcast Host

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Recent Guests

Pierpaolo Hipolito
Data scientist at SAS Institute and contributor to Towards Data Science
SAS Institute
Episode: Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183
Michael Berk
Data scientist specializing in A/B testing and machine learning applications.
Tubi
Episode: A/B Testing with ML ft. Michael Berk - ML 181
Rishal Hurbans
Author of Grokking Artificial Intelligence Algorithms
Manning
Episode: The Nature of the World and AI with Rishal Hurbans - ML 177
Brian Vallelunga
CEO of Doppler
Doppler
Episode: Innovative Security Solutions for Developers - ML 174
Artem Koren
Chief Product Officer at Sembly AI
Sembly AI
Episode: AI-Powered Tools for Productivity with Artem Koren - ML 169
Hikari Senju
CEO of Omneky, an AI-driven marketing asset developer
Omneky
Episode: The Impact of Generative AI on the Advertising Industry - ML 168
Luis Garcia
Co-founder of Collectiva, an organization offering fractional executive services for game tech startups
Collectiva
Episode: AI in Education: From Micro-Courses to Rigorous Training Programs - ML 162
Keith A. Goode
VP of Services at Zeroed-in, experienced across various roles in the tech field.
Zeroed-in
Episode: Transforming Recruitment with AI: Surveys, Sentiment, and Data-Driven Insights - ML 161
Brad Micklea
Founder and CEO of Jozu, with extensive experience in software infrastructure and machine learning operations.
Jozu
Episode: AI Deployment Simplified: Kit Ops' Role in Streamlining MLOps Practices - ML 159

Hosts

Michael Berk
Co-host specializing in machine learning applications and a data scientist with hands-on experience in A/B testing and machine learning implementations.
Ben Wilson
Co-host with a focus on machine learning and its applications, possessing extensive knowledge in data science and technology integration.
Charles Max Wood
Host with a background in machine learning and technology discussions, contributing expertise from his experience in plant-based AI projects.

Reviews

4.9 out of 5 stars from 33 ratings
  • resume chucks spam not good stick to podcasts only

    not good stick to making only podcast. don’t give out false information for subscription services. resume never comes. easily ads turning into spam in user emails and multiple false positives

    Apple Podcasts
    1
    JVo12
    Canada2 years ago
  • ML Leaps and Bounds

    Some good insight into the realities of being a machine learning engineer.

    Apple Podcasts
    5
    yogastud
    United States3 years ago
  • Great info!

    A must-listen for anyone in the machine learning space and beyond :)

    Apple Podcasts
    5
    malloryck
    United States3 years ago
  • Super Insightful

    I love this show. The guests that they bring on are incredibly interesting and provide some great insight.

    Apple Podcasts
    5
    EllieB_18
    United States3 years ago
  • Personal fave

    Love this show and the interviews they host!! 🦊♥️

    Apple Podcasts
    5
    SavPoi
    United States3 years ago

Listeners Say

Key themes from listener reviews, highlighting what works and what could be improved about the show.

The series is recognized for hosting interesting guests who provide valuable expertise and insights into the field of machine learning.
However, some have expressed frustration over certain episodes feeling promotional rather than informative.
Some listeners appreciate the insightful and practical discussions on machine learning, noting how the content is relevant to their professional needs.

Chart Rankings

How this podcast ranks in the Apple Podcasts, Spotify and YouTube charts.

Apple Podcasts
#166
Saudi Arabia/Technology
Apple Podcasts
#213
Denmark/Technology
Apple Podcasts
#217
Poland/Technology

Talking Points

Recent interactions between the hosts and their guests.

Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183
Q: How can data scientists avoid the accuracy paradox while ensuring model effectiveness?
Make sure there's a good balance between classes and use precision and recall metrics to guide you, rather than focusing solely on accuracy.
Navigating Common Pitfalls in Data Science: Lessons from Pierpaolo Hipolito - ML 183
Q: What prompted you to write the article on data science paradoxes?
The idea came from my master's research on causality in machine learning, specifically focusing on how incorrect interpretations of data can lead to issues in modeling.
A/B Testing with ML ft. Michael Berk - ML 181
Q: How do you convince industries that are not using A/B testing to adopt these practices?
Highlight the importance of empirical evidence in proving causality, emphasizing that A/B testing is the gold standard in data-driven decision-making.
A/B Testing with ML ft. Michael Berk - ML 181
Q: What does successful A/B testing look like in your projects?
Looking at the empirical distribution of experiment lifts tends to show that a small number of experiments drive a significant amount of lift, in line with the 80-20 rule.
The Nature of the World and AI with Rishal Hurbans - ML 177
Q: How do you start thinking about different algorithms?
The concept of old AI and new AI is crucial, with old AI relying on well-defined rules and new AI using more flexible approaches for unstructured data.

Audience Metrics

Listeners, social reach, demographics and more for this podcast.

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Frequently Asked Questions About Adventures in Machine Learning

What is Adventures in Machine Learning about and what kind of topics does it cover?

A series dedicated to exploring the field of machine learning, engaging expert hosts and guests who share insights, best practices, and personal experiences centered around practical applications in technology. The discussions focus on a diverse array of relevant topics such as A/B testing, data governance, model serving, and the implications of AI technology in business decisions. Notably, the series emphasizes real-world applications and explores critical challenges that professionals face in the rapidly evolving landscape of machine learning technology. This educational platform is suited for individuals looking to deepen their understanding and navigate their careers in artificial intelligence and machine learning sectors.

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Which podcasts are similar to Adventures in Machine Learning?

These podcasts share a similar audience with Adventures in Machine Learning:

1. Practical AI
2. Data Skeptic

How many episodes of Adventures in Machine Learning are there?

Adventures in Machine Learning launched 5 years ago and published 209 episodes to date. You can find more information about this podcast including rankings, audience demographics and engagement in our podcast database.

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What guests have appeared on Adventures in Machine Learning?

Recent guests on Adventures in Machine Learning include:

1. Pierpaolo Hipolito
2. Michael Berk
3. Rishal Hurbans
4. Brian Vallelunga
5. Artem Koren
6. Hikari Senju
7. Luis Garcia
8. Keith A. Goode

To view more recent guests and their details, simply upgrade your Rephonic account. You'll also get access to a typical guest profile to help you decide if the show is worth pitching.

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