Voxel = 3d pixel

I took GPT-2 and trained it on r/ShowerThoughts. The site has a static list of generated responses that it serves at random from.

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Hyperparameters: Adam w/ lr=1e-5, batch size 16, sample length 255. Trained for 4000 iterations.

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https://eukaryote31.github.io/bot-thoughts/

https://blog.pocketcluster.io/category/index/

New article written by Andrej Karpathy distilling a bunch of useful heuristics for training neural nets. I think the blog post is full of the kind of real-world knowledge and how-to details that are not taught in books and often take endless hours to learn the hard way.

Have a look:

https://karpathy.github.io/2019/04/25/recipe/

I built a Neural Network model (using Python and TensorFlow) for forecasting stock prices in 2016 and used the algorithm in my hedge fund in 2017. I made a video which provides a step-by-step walk through for how to create, train, and evaluate the model for the the purpose of generating buy and sell signals for financial securities.

The methodology should be very useful for anyone looking to build something like this.

This example utilizes a four layer neural network for trading volatility ETPs but can be easily modified to include other securities and metrics as predictor inputs.

I just stumbled across this enterprise product h2o ai, and while I’m not really too interested in their auto-ai solutions, it does look like they have some nice tools to visualize datasets, outliers, and missing values.

For those who work with their own datasets, I was wondering what tools you all use to accomplish this? I suppose I could build my own, but if there’s existing (preferably free) platforms to do something similar, that’d be awesome.

Hi guys, I’m part of a research group trying to use Natural Language Processing to recognize dog breeds based on a verbal input. However, to train our model, we need to build a dataset, so I would really appreciate it if y’all could fill out this google form:

https://docs.google.com/forms/d/e/1FAIpQLSdTATkD1Ulw-zjshzIQIt6bbmnL1UvfHHprnK3JJrAnx98YgA/viewform

Thanks!