6 lies you have been told about machine learning:
1. You need a lot of math to start
2. You need a Ph.D. to get a job
3. You always need a lot of data
4. You need to buy expensive hardware
5. It's hard to become proficient in it
6. It's the solution for most problems
Bullshit.
1. You need a lot of math to start
2. You need a Ph.D. to get a job
3. You always need a lot of data
4. You need to buy expensive hardware
5. It's hard to become proficient in it
6. It's the solution for most problems
Bullshit.
In the last 6 months, I've posted more than 100 threads here on Twitter talking about machine learning and how you can build a career on it.
And I'm just getting started!
Stay tuned. A lot more is coming.
And I'm just getting started!
Stay tuned. A lot more is coming.
First misconception: All machine learning is hardware-hungry.
Deep learning stretches you, but outside that, it gets much better.
If you need GPUs/TPUs, there are many free/cheap options you can use, especially while learning.
Deep learning stretches you, but outside that, it gets much better.
If you need GPUs/TPUs, there are many free/cheap options you can use, especially while learning.
https://twitter.com/jhonyfuza/status/1403646252173119489?s=20
For some reason, many people believe we need an insane amount of data to solve anything.
Reality: Some problems require very little data to achieve excellent results.
With transfer learning, few-shot, one-shot, and zero-shot learning even more.
Reality: Some problems require very little data to achieve excellent results.
With transfer learning, few-shot, one-shot, and zero-shot learning even more.
https://twitter.com/nmmanas/status/1403658015312470019?s=20
It’s a little bit different on different countries.
Here in the states, more and more positions are coming out and they aren’t asking for a PhD.
It will get even better over time.
Here in the states, more and more positions are coming out and they aren’t asking for a PhD.
It will get even better over time.
https://twitter.com/anusiemjohn/status/1404000014901334018
Great suggestion!
Machine learning is a big field.
Niching down in one specific domain is smart and will increase your odds at building a successful career.
Machine learning is a big field.
Niching down in one specific domain is smart and will increase your odds at building a successful career.
https://twitter.com/LorenzoLegacy/status/1404093393442123780?s=20
This has been my experience:
• When learning, Google Colab and Kaggle give me all the hardware I need.
• When working on more complex, serious stuff, a company pays for the hardware.
Result: I have never owned a GPU and have never needed it to spend more electricity at home.
• When learning, Google Colab and Kaggle give me all the hardware I need.
• When working on more complex, serious stuff, a company pays for the hardware.
Result: I have never owned a GPU and have never needed it to spend more electricity at home.
Why do people think that "proficient" means "knowing anything and everything"?
Do you know anyone that fits this description?
Proficient, in my book, is having the ability to provide value and make money off your work.
No, you don't need to understand everything to get there.
Do you know anyone that fits this description?
Proficient, in my book, is having the ability to provide value and make money off your work.
No, you don't need to understand everything to get there.
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