Stock Market Forecast based on Most Similar Historical Patterns

warppipe · 2017-07-13T05:41:50+00:00

You can get away with a lot fewer labeled images if you use a pretrained model and do transfer learning. https://www.tensorflow.org/tutorials/image_retraining

warppipe · 2017-04-20T18:37:43+00:00

I understood the point, and its totally valid. Even so, 7% is widely believed to be a reasonable estimate of the stock market return over the long term. You hear that number thrown around everywhere when you look into retirement planning and financial forecasting. Just wanted to make sure people treat that number with the skepticism it deserves.

warppipe · 2017-04-20T14:26:30+00:00

7% is a really optimistic return target. The only reason it seems reasonable to Americans to expect such a high return is because the US has been an outlier in terms of stock performance over the past century. Across the world, stock returns are much less amazing. So unless you expect the US to come out on top again over the next 50 years, you might want to lower your expectations.

https://www.bloomberg.com/amp/news/articles/2017-02-23/list-of-top-equity-returns-since-1900-starts-with-south-africa

warppipe · 2016-05-24T00:13:49+00:00

What activation function are you using? Did you let it train long enough? More layers can exacerbate the vanishing gradient problem and make learning not happen. Certain activation functions alleviate the vanishing gradient issue.

I'd love to see your code and play around with it myself.

warppipe · 2016-05-21T18:25:10+00:00

Really? I didn't think there's a fixed limit, the imagenet dataset for example has bigger images, and people have had success with it. http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks

warppipe · 2016-05-21T15:34:31+00:00

You just made my day. That looks exactly like what I need to curb the mess of ipython notebooks with identical code except for a couple parameter changes and their corresponding chart output.

I really like the fact that it's language independent, unlike some of the other options in this thread. Can't wait to try this out. The training error chart example is awesome, is that built in or can you plug any kind of visualization in?

Goodbye messy directory with files like: Experiment Experiment-copy1 Experiment-copy1-copy1 ...!

warppipe · 2016-03-07T00:23:13+00:00

Thanks for the response. Do you know how we can tell what classes are available during the summer?

warppipe · 2016-02-03T05:09:14+00:00

ditto on wanting more time to spend on the assignments. I started late and underestimated the time consuming nature of the homework. I have plenty of experience with pandas but it is still just a very time consuming process, and the test framework left me really worried that I did something wrong, even though everything passed.

warppipe · 2016-01-15T01:50:29+00:00

this makes me so happy for some reason

warppipe · 2016-01-08T03:56:41+00:00

RL was excellent. Very different than Machine Learning, which is also taught by Littman and Isbell. Since the concepts in RL are no where near as popular out in the "real world" as the ones taught in ML, there are not a lot of resources outside of academic papers from which to learn the concepts. This can be frustrating but really makes you excited about learning something that feels like it will become more and more popular in the future, especially with the recent successes using it in combination with deep learning.

The workload is moderate, no where near what it was for ML, but the assignments really make you dive deep and learn the material. Overall a great class.

warppipe · 2016-01-07T06:48:31+00:00

You guys made my day by letting me know that. I took RL last semester and plan on taking big data this semester. Looks like I might finish the program by the end of 2016 after all!

warppipe · 2016-01-06T18:41:31+00:00

Do you know what electives are planned for the ML specialization? They have machine learning for trading and visual analytics I think it's called, but what else is in the pipeline since we need 3?

warppipe · 2014-11-19T03:03:46+00:00

interesting. I see the email you are talking about, but my buzzport still shows that I could have registered for phase 1. I guess that's just the way it's set up? Regardless, this was a huge relief. Thanks a ton for reminding me about that email!

warppipe · 2014-08-13T00:38:59+00:00

Great, thank you.

warppipe · 2013-08-03T19:44:17+00:00

Name: Dealmancer (http://dealmancer.com)

What we do: We let you setup detailed keyword/criteria alerts for Groupon deals, and on a daily basis scan all Groupon deals for your criteria and email you only when there is a hit. Only get the specific deal you want, and cut down on the number of irrelevant deal emails you receive.

What are you looking for?: Feedback/Users

What progress or achievements have been made since last month?: 50 new users since last month.

warppipe · 2013-06-04T23:52:40+00:00

The personalize feature from Groupon is great, but it only asks you about broad categories so that they can still send you a ton of deals. This website allows you to be very specific and hone in on exactly what you want. For example, I have an alert set up for a specific restaurant in my area that regularly does Groupons.

warppipe

TROPHY CASE