Understanding Tensorflow's tensors shape: static and dynamic
Describing computational graphs is just a matter connecting nodes correctly. Connecting nodes seems a trivial operation, but it hides some difficulties related to the shape of tensors. This article will guide you through the concept of tensor's shape in both its variants: static and dynamic.Camera calibration guidelines
The process of geometric camera calibration (camera resectioning) is a fundamental step for machine vision and robotics applications. Unfortunately, the result of the calibration process can vary a lot depending on various factors. There are a lot of empirical guidelines that have to be followed in order to achieve good results: this post will drive you through them.Ethereum on Raspberry Pi: secure wallet and complete node with redundant storage
Ethereum is a relatively new player in the crypto-currencies ecosystem. If you are a researcher, an algorithmic trader or an investor, you could want to run an ethereum node to study, develop and store your ETH while contributing to the network good.Understanding Tensorflow using Go
Tensorflow is not a Machine Learning specific library, instead, is a general purpose computation library that represents computations with graphs. Its core is implemented in C++ and there are also bindings for different languages. The bindings for the Go programming language, differently from the Python ones, are a useful tool not only for using Tensorflow in Go but also for understanding how Tensorflow is implemented under the hood.
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