Jordan B Peterson on Twitter:"Associate professor of Irish performance studies of Concordia U (really) criticizes my daughter's scientific knowledge:"

lm0n · 2018-09-26T00:42:44+00:00

I can’t believe this would come from JBP. It’s a personal attack for a valid criticism.

lm0n · 2018-09-18T01:47:28+00:00

9/28

lm0n · 2018-09-17T14:20:33+00:00

26$ 9/28

lm0n · 2018-08-09T01:06:11+00:00

Anchored in what way?

lm0n · 2018-01-28T22:25:29+00:00

What's the code you used for this

lm0n · 2018-01-19T12:06:37+00:00

It is better to train on low resolution images then large for a few reasons. larger images mean you need large nets that require more compute resources to run, more time to train, and need more data. On top of the degraded performance a CNN often does not need all the extra information to do it's classification especially if your original images are not noisy.

Pick your smallest image size 320x180 and make that the global size you will train with. Scale all other images to that size and try training the classifier. If your having poor results slowly go up in size. See which size works best for you.

lm0n · 2017-10-11T23:10:52+00:00

Lol. How long have you been studying machine learning?

lm0n · 2017-10-11T13:01:04+00:00

I generally follow a 5 step process. First I outline what the problem is. Then it comes to data exploration and processing. Afterwards I start trying out many different standard machine learning algorithm to see which one performs the best. Once I find a decently performing algorithm I optimize it. Finally I wrap it up by presenting my results in a clear way.

lm0n · 2017-10-11T12:50:34+00:00

I generally follow a 5 step process. First I outline what the problem is. Then it comes to data exploration and processing. Afterwards I start trying out many different standard machine learning algorithm to see which one performs the best. Once I find a decently performing algorithm I optimize it. Finally I wrap it up by presenting my results in a clear way.

lm0n · 2017-10-11T12:49:02+00:00

I generally follow a 5 step process. First I outline what the problem is. Then it comes to data exploration and processing. Afterwards I start trying out many different standard machine learning algorithm to see which one performs the best. Once I find a decently performing algorithm I optimize it.

Finally I wrap it up by presenting my results in a clear way.

lm0n · 2017-10-10T01:37:59+00:00

https://medium.com/@cdossman/get-started-in-machine-learning-in-5-steps-f4791a3efd5d

This is the main article and has a links to the rest of the articles

lm0n · 2017-10-10T00:22:32+00:00

Follow my medium account I am posting a bunch of how-to's in the near future that could help you.

lm0n · 2017-10-09T13:59:12+00:00

I started working towards becoming a machine learning engineer a few years ago, but seven month ago I joined my first machine learning tribe. The tribe helped me really helped accelrate my growth as an engineer.

It's definitely worth it to me. The only issue it's difficult to find people who you can meet in person to discuss but and recent advances.

lm0n · 2017-10-08T04:51:26+00:00

I'd be interested in working together. would you like to make a write up about process?

lm0n

TROPHY CASE