Join our MCubed web lecture this week to find out how to get machine learning into production
DISCLAIMER: This blog is fully automated, unmonitored, and does not reflect the views of Garett MacGowan. The ML model may produce content that is offensive to some readers.
This blog post was generated with a (potentially) real article title as the only prompt. A link to the original article is below.
Photo by Zoltan Tasi on Unsplash
Generated: 10/6/2021
Join our MCubed web lecture this week to find out how to get machine learning into production mode for your real business problems.
We'll look at three questions you might have as a machine learning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
See a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.
About the presenter
Tom Minka is a software engineer in New York City who has worked at Amazon, Netflix, and Apple, and on multiple open-source machine learning projects. He's also a co-author of Python Machine Learning in Action.
You might have seen Tom on the MCubed blog or our web seminars, or just read his articles.
But be sure to see him on a screen near you soon in NYC!
Lecture videos
On our web lecture platform, we use OVA to deliver the best possible experience. Because of DRM constraints, you must have JavaScript enabled to watch on the website.
If you can't see the video and want to attend in person, we're presenting live this week at DevOps Summit in Nashville.
See you there.Join our MCubed web lecture this week to find out how to get machine learning into production mode for your real business problems.
We'll look at three questions you might have as a machine learning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
See a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.
About the presenter
Tom Minka is a software engineer in New York City who has worked at Amazon, Netflix, and Apple, and on multiple open-source machine learning projects. He's also a co-author of Python Machine Learning in Action.
You might have seen Tom on the MCubed blog or our web seminars, or just read his articles.
But be sure to see him on a screen near you soon in NYC!
Lecture videos
On our web lecture platform, we use OVA to deliver the best possible experience. Because of DRM constraints, you must have JavaScript enabled to watch on the website.
If you can't see the video and want to attend in person, we're presenting live this week at DevOps Summit in Nashville.
See you there.arning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
See a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.
About the presenter
Tom Minka is a software engineer in New York City who has worked at Amazon, Netflix, and Apple, and on multiple open-source machine learning projects. He's also a co-author of Python Machine Learning in Action.
You might have seen Tom on the MCubed blog or our web seminars, or just read his articles.
But be sure to see him on a screen near you soon in NYC!
Lecture videos
On our web lecture platform, we use OVA to deliver the best possible experience. Because of DRM constraints, you must have JavaScript enabled to watch on the website.
If you can't see the video and want to attend in person, we're presenting live this week at DevOps Summit in Nashville.
See you there.Join our MCubed web lecture this week to find out how to get machine learning into production mode for your real business problems.
We'll look at three questions you might have as a machine learning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
See a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCswers to each of them.
Watch a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.
About the presenter
Anand Kumar is a passionate machine learning engineer who likes to experiment with ideas, algorithms, and applications. He is an alumnus of Indian Institute of Technology, Bombay and currently works as a Machine Learning Solutions Architect within a product division at Google. You might have seen Anand on the MCubed blog or our web seminars, or just read his articles.
But be sure to see him on a screen near you soon in Seattle!
Lecture videos
On our web lecture platform, we use OVA to deliver the best possible experience. Because of DRM constraints, you must have JavaScript enabled to watch on the website.
If you can't see the video and want to attend in person, we're presenting live this week at DevOps Summit in Seattle — and it's free! Join us.
See you there.Join our MCubed web lecture this week to find out how to get machine learning into production mode for your real business problems.
We'll look at three questions you might have as a machine learning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
Watch a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.
We'll look at three questions you might have as a machine learning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
See a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.
About the presenter
Tom Minka is a software engineer in New York City who has worked at Amazon, Netflix, and Apple, and on multiple open-source machine learning projects. He's also a co-author of Python Machine Learning in Action.
You might have seen Tom on the MCubed blog or our web seminars, or just read his articles.
But be sure to see him on a screen near you soon in NYC!
Lecture videos
On our web lecture platform, we use OVA to deliver the best possible experience. Because of DRM constraints, you must have JavaScript enabled to watch on the website.
If you can't see the video and want to attend in person, we're presenting live this week at DevOps Summit in Nashville.
See you there.Join our MCubed web lecture this week to find out how to get machine learning into production mode for your real business problems.
We'll look at three questions you might have as a machine learning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
See a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.
About the presenter
Tom Minka is a software engineer in New York City who has worked at Amazon, Netflix, and Apple, and on multiple open-source machine learning projects. He's also a co-author of Python Machine Learning in Action.
You might have seen Tom on the MCubed blog or our web seminars, or just read his articles.
But be sure to see him on a screen near you soon in NYC!
Lecture videos
On our web lecture platform, we use OVA to deliver the best possible experience. Because of DRM constraints, you must have JavaScript enabled to watch on the website.
If you can't see the video and want to attend in person, we're presenting live this week at DevOps Summit in Nashville.
See you there.arning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
See a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.
About the presenter
Tom Minka is a software engineer in New York City who has worked at Amazon, Netflix, and Apple, and on multiple open-source machine learning projects. He's also a co-author of Python Machine Learning in Action.
You might have seen Tom on the MCubed blog or our web seminars, or just read his articles.
But be sure to see him on a screen near you soon in NYC!
Lecture videos
On our web lecture platform, we use OVA to deliver the best possible experience. Because of DRM constraints, you must have JavaScript enabled to watch on the website.
If you can't see the video and want to attend in person, we're presenting live this week at DevOps Summit in Nashville.
See you there.Join our MCubed web lecture this week to find out how to get machine learning into production mode for your real business problems.
We'll look at three questions you might have as a machine learning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
See a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCswers to each of them.
Watch a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.
About the presenter
Anand Kumar is a passionate machine learning engineer who likes to experiment with ideas, algorithms, and applications. He is an alumnus of Indian Institute of Technology, Bombay and currently works as a Machine Learning Solutions Architect within a product division at Google. You might have seen Anand on the MCubed blog or our web seminars, or just read his articles.
But be sure to see him on a screen near you soon in Seattle!
Lecture videos
On our web lecture platform, we use OVA to deliver the best possible experience. Because of DRM constraints, you must have JavaScript enabled to watch on the website.
If you can't see the video and want to attend in person, we're presenting live this week at DevOps Summit in Seattle — and it's free! Join us.
See you there.Join our MCubed web lecture this week to find out how to get machine learning into production mode for your real business problems.
We'll look at three questions you might have as a machine learning practitioner:
How should I prepare my data?
How should I create my models?
How do I decide what's important enough to spend my hard work on?
And we'll give you actionable answers to each of them.
Watch a demonstration on the presenter's screen and click a link below to attend in person or join online.
You can also watch the recording for more detail on any parts you don't understand — or share with colleagues.
Questions, comments?
Learn better skills than the rest, by understanding the most important concepts first. That's what the MCubed lecture series is here to help you with.