Types of Neural Networks

The other day, I decided to read one paper about neural networks a day. I chose publications available at Arxiv and I added the site to my RSS reader. And just two days later I was shocked by the number of papers submitted to Arxiv every day! There were so many new ideas in the field of neural networks that it was impossible to follow them all. I gave up this habit after a week, but I realized one important thing: the majority of these papers were related to tuning or modifying already existing types of neural networks.

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11 weeks of effective learning

The course named “Machine Learning”, created by Professor Andrew Ng is one of the most popular courses on the Internet. Since its first publication, more than 8 million learners have signed up. Initially, the course was available on YouTube but after some time it has been moved to Coursera.

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Aligning, resizing and normalization

It’s time to start implementing support for recognizing gestures with neural networks. As I mentioned in the previous post, I had seen some potential problems. After two days of work, I can finally write that those problems are solved. In this post, I’ll describe how I solved the problem of different drawing area location. In the second paragraph, I’m going to describe implemented resizing strategy. At the end, in the third part, I’ll write some words about flattering gestures and values normalization.

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Artificial Intelligence on the board

In the previous post, I mentioned that the next thing developed in the Aksesi project will be a management console. After submitting that post, I realized that it is going to be another boring application with 90% of its logic encapsulated in CRUD operations. When I decided to take part in Get Noticed competition, my main goal was to learn new things. To make a long story short. The next step won’t be management console; the next step will be gesture recognition with Artificial Intelligence usage.

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