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Todd Nief's Show

Todd Nief

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Todd Nief's Show
Todd Nief's Show

Todd Nief's Show

Todd Nief

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Followers
1
Plays
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About Us

Todd Nief's Show is about unpacking the models that people use to think about the world and solve problems in complex areas like fitness, business, nutrition, music, and academia.

Latest Episodes

Chelsea Troy

Chelsea Troy is a self-taught and informally educated software engineer and data scientist who also specializes in machine learning. Chelsea also blogs regularly at www.chelseatroy.com. In this conversation, we discuss the process of self-educating in a variety of software-related disciplines, the state of machine learning and whether or not its going to swallow our society, and how technology companies can improve diversity in their workforces - both in terms of tangible actions for employees and managers as well as higher-level organizational changes. Check out more from Chelsea here: Instagram: @misschelseatroy Website: www.chelseatroy.com If you're enjoying the show, the best way to support it is by sharing with your friends. If you don't have any friends, why not a leave a review? It makes a difference in terms of other people finding the show. You can also subscribe to receive my e-mail newsletter at www.toddnief.com. Most of my writing never makes it to the blog, so get on that list. Show Notes: [0:07] Self-educating in software development and data science through a project-based approach – and the strengths and weaknesses of project-based learning vs a formal academic model [08:48] Almost all of your time in software development is spent at the margin of what you know how to do, so you have to be comfortable with being uncomfortable. Improvement often comes through bettering your ability to solve the inevitable problems that you will run into. [19:12] Reduce the feedback loop as much as possible and create testing scenarios in order to rapidly iterate on software. One weird trick to learning software development: copy the changes that more experienced developers make to their code by hand [30:30] The best learning comes from realizing that you’ve made a mistake. Having a generalist approach and understanding multiple programming languages enables solving problems in non-traditional ways. [37:42] Should we believe the hype on machine learning? What will be the future of machine learning and how will humans work with this technology as we are able to automate more and more tasks and better recognize patterns in data? [48:02] The dangers of algorithmic recommendations and the amount of resources going into increasing advertisement clicks through machine learning. Can we have machine learning algorithms make their decisions and categorizations “human legible”? [1:03:07] How can tech companies move the needle on diversity in hiring? What actionable communication and management behaviors can individuals employ in terms of making technical companies more welcoming to underrepresented folks? [1:14:07] How do we get more viewpoint diversity in the upper echelons of technology companies? Viewpoint diversity seems to clearly help companies improve performance, but can be painful and create more conflict within the organization. Links and Resources Mentioned John Conway's Game of Life Deliberate practice What is the difference between FragmentPagerAdapter and FragmentStatePagerAdapter? GitHub Pivotal Labs “Leveling Up Skill #6: Commit Tracing” from Chelsea Troy Zooniverse Hubble Telescope Hanny's Voorwerp Janelle Shane “Try these neural network-generated recipes” from Janelle Shane “Do neural nets dream of electric sheep?” from Janelle Shane “Metal band names invented by neural network” from Janelle Shane “The neural network has weird ideas about what humans like to eat” from Janelle Shane (this one kills me) Decision tree learning Game of Thrones

89 MIN1 weeks ago
Comments
Chelsea Troy

Survivorship Bias & Bad Advice

People enjoy listening to successful people explain how they were able to achieve the things that they’ve accomplished. (I should know, I often interview them). Unfortunately, a lot of advice from successful people is absolutely terrible. It fails to take into account the thousands and thousands of other people who “dedicated their life to their passion,” “sacrificed everything to make themselves better,” “did a great job and focused on their product,” and “pushed themselves to work harder every day.” When we only focus on those who made it, this is called “survivorship bias” and it leads to some pretty unfortunate errors and, particularly in athletics and business, a toxic form of magical thinking. Cut it out! If you're enjoying the show, the best way to support it is by sharing with your friends. If you don't have any friends, why not a leave a review? It makes a difference in terms of other people finding the show. You can also subscribe to receive my e-mail newsletter at www.toddnief.com. Most of my writing never makes it to the blog, so get on that list.

40 MIN3 weeks ago
Comments
Survivorship Bias & Bad Advice

Marcus Filly (Revival Strength)

Marcus Filly is the owner of Revival Strength and Revive-Rx, as well as a multiple time CrossFit Games athlete. Marcus has popularized the concept of Functional Bodybuilding and a more measured approach to intensity in fitness training - especially for people whose goal is to look good, feel good and move well (not necessarily compete at a high level). Marcus is a highly analytical individual, and we discuss finding the balance between being systematic and going with the flow, creating content for yourself and creating content for an audience, and many hilarious stories from training with Danny Nichols and the GRID League. Check out more from Marcus, Revival Strength & Functional Bodybuilding here: Instagram: @marcusfilly//@functional.bodybuilding//@revivalstrength Website: www.functionalbodybuilding.net//www.revival-strength.com (Sign up for Marcus’s e-mail list here!)//www.revive-rx.com Podcast: Look Good, Move Well Podcast Show Notes [01:51] The differences between posting train...

71 MINMAY 17
Comments
Marcus Filly (Revival Strength)

Latest Episodes

Chelsea Troy

Chelsea Troy is a self-taught and informally educated software engineer and data scientist who also specializes in machine learning. Chelsea also blogs regularly at www.chelseatroy.com. In this conversation, we discuss the process of self-educating in a variety of software-related disciplines, the state of machine learning and whether or not its going to swallow our society, and how technology companies can improve diversity in their workforces - both in terms of tangible actions for employees and managers as well as higher-level organizational changes. Check out more from Chelsea here: Instagram: @misschelseatroy Website: www.chelseatroy.com If you're enjoying the show, the best way to support it is by sharing with your friends. If you don't have any friends, why not a leave a review? It makes a difference in terms of other people finding the show. You can also subscribe to receive my e-mail newsletter at www.toddnief.com. Most of my writing never makes it to the blog, so get on that list. Show Notes: [0:07] Self-educating in software development and data science through a project-based approach – and the strengths and weaknesses of project-based learning vs a formal academic model [08:48] Almost all of your time in software development is spent at the margin of what you know how to do, so you have to be comfortable with being uncomfortable. Improvement often comes through bettering your ability to solve the inevitable problems that you will run into. [19:12] Reduce the feedback loop as much as possible and create testing scenarios in order to rapidly iterate on software. One weird trick to learning software development: copy the changes that more experienced developers make to their code by hand [30:30] The best learning comes from realizing that you’ve made a mistake. Having a generalist approach and understanding multiple programming languages enables solving problems in non-traditional ways. [37:42] Should we believe the hype on machine learning? What will be the future of machine learning and how will humans work with this technology as we are able to automate more and more tasks and better recognize patterns in data? [48:02] The dangers of algorithmic recommendations and the amount of resources going into increasing advertisement clicks through machine learning. Can we have machine learning algorithms make their decisions and categorizations “human legible”? [1:03:07] How can tech companies move the needle on diversity in hiring? What actionable communication and management behaviors can individuals employ in terms of making technical companies more welcoming to underrepresented folks? [1:14:07] How do we get more viewpoint diversity in the upper echelons of technology companies? Viewpoint diversity seems to clearly help companies improve performance, but can be painful and create more conflict within the organization. Links and Resources Mentioned John Conway's Game of Life Deliberate practice What is the difference between FragmentPagerAdapter and FragmentStatePagerAdapter? GitHub Pivotal Labs “Leveling Up Skill #6: Commit Tracing” from Chelsea Troy Zooniverse Hubble Telescope Hanny's Voorwerp Janelle Shane “Try these neural network-generated recipes” from Janelle Shane “Do neural nets dream of electric sheep?” from Janelle Shane “Metal band names invented by neural network” from Janelle Shane “The neural network has weird ideas about what humans like to eat” from Janelle Shane (this one kills me) Decision tree learning Game of Thrones

89 MIN1 weeks ago
Comments
Chelsea Troy

Survivorship Bias & Bad Advice

People enjoy listening to successful people explain how they were able to achieve the things that they’ve accomplished. (I should know, I often interview them). Unfortunately, a lot of advice from successful people is absolutely terrible. It fails to take into account the thousands and thousands of other people who “dedicated their life to their passion,” “sacrificed everything to make themselves better,” “did a great job and focused on their product,” and “pushed themselves to work harder every day.” When we only focus on those who made it, this is called “survivorship bias” and it leads to some pretty unfortunate errors and, particularly in athletics and business, a toxic form of magical thinking. Cut it out! If you're enjoying the show, the best way to support it is by sharing with your friends. If you don't have any friends, why not a leave a review? It makes a difference in terms of other people finding the show. You can also subscribe to receive my e-mail newsletter at www.toddnief.com. Most of my writing never makes it to the blog, so get on that list.

40 MIN3 weeks ago
Comments
Survivorship Bias & Bad Advice

Marcus Filly (Revival Strength)

Marcus Filly is the owner of Revival Strength and Revive-Rx, as well as a multiple time CrossFit Games athlete. Marcus has popularized the concept of Functional Bodybuilding and a more measured approach to intensity in fitness training - especially for people whose goal is to look good, feel good and move well (not necessarily compete at a high level). Marcus is a highly analytical individual, and we discuss finding the balance between being systematic and going with the flow, creating content for yourself and creating content for an audience, and many hilarious stories from training with Danny Nichols and the GRID League. Check out more from Marcus, Revival Strength & Functional Bodybuilding here: Instagram: @marcusfilly//@functional.bodybuilding//@revivalstrength Website: www.functionalbodybuilding.net//www.revival-strength.com (Sign up for Marcus’s e-mail list here!)//www.revive-rx.com Podcast: Look Good, Move Well Podcast Show Notes [01:51] The differences between posting train...

71 MINMAY 17
Comments
Marcus Filly (Revival Strength)

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