here is my question in quora

https://www.quora.com/Why-is-RNN-less-progress-research-than-CNN-especially-the-time-series

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question is

Why is RNN less progress research than CNN (especially the time series)?

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and answer is

Any problem concerning the images is incredibly harder than that concerns a time series. This is why the research on CNN and its derivatives (U-Net, GAN) are still continuing.

The research on how to deal with time-series data is almost finished. It looks like researchers are trying to come up with better and better techniques, but what is actually happening is people are trying to predict dependencies that are actually not present in the data or using insufficient data!

A good example is the stock value prediction. The simple truth is that the stock prices depend on many more variables that are not present in the typical input time series’ used with RNN or LSTM.

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My personal opinion is now LSTM is SOTA but I think another SOTA network will be created.

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how about think of this topic?

Hi everyone,

I’m those host of the All Things Interesting Podcast and wanted to drop in to share my first interview with blockchain startup technical cofounder Kasian Franks.

Kasian and his team at Vectorspace AI are working on bridging blockchain with context controlled vector based NLP/NLU to power AI and machine learning. In this episode, we talk about all things AI, ML, NLP/NLU, and blockchain.

All Things Interesting Podcast #1: Kasian Franks of Vectorspace AI

Good day!

Here’s an article I wrote on setting up Amazon SageMaker with Terraform, based on the example from AWS Solutions.

https://medium.com/@qtangs/machine-learning-infrastructure-with-amazon-sagemaker-and-terraform-a-case-of-fraud-detection-ab6896144781

Source code can be found here: https://github.com/qtangs/tf-fraud-detection-using-machine-learning

I’d love to hear feedback from the community.

Please note, though, that I’m a noob in machine learning, so pardon my ignorance in many areas.

Original AWS example: https://aws.amazon.com/solutions/fraud-detection-using-machine-learning/

Thanks!

I’m going to a 2 day machine learning hackathon. 2 days isn’t a lot of time to train a brand new model, so I’m hoping to make something that would assist other ML people. 2 days will probably just be enough time for a prototype with core functionality.

If it makes a difference, I’ll be working in Pytorch.

I’m at ACL this week and some people give way better conference talks than others. Professors and keynote speakers I get, they have had a lot of practice. But how do people who are PhD students get so good at giving talks? e.g. Sebastien Mielke or Angela Fan

Reddit, What are your tips for me?

Deployed Web App

Source Code

Model Explanation

Hi all! I graduated with a BS in computer science last spring and have spent the last few months building and deploying my first large-scale ML project. I would love to hear any feedback or criticism you have to offer. Thanks!