Comparing productivity of node.js frameworks

Our mission is to compare the node.js frameworks on productivity.

In one of my previous blogs I have benchmark the various node.js frameworks performance against native http call and native mongodb driver and native combination was clear winner in term of performance.

https://blog.talentica.com/2017/11/14/comparing-performance-of-node-js-frameworks/

so, Why not use only native http and native mongodb driver. well one of the the key aspect and usp of node.js frameworks is that they provide lot of abstractions and as a developer you don’t have to write boiler plate , repetitive code . so lets see what our research has come up with against this concept. Continue reading

Comparing performance of node.js frameworks

Our mission is to compare the node.js frameworks on performance (completed no of requests per second).

Node.js performance tests were performed on the Ubuntu subsystem(2 core , 2 GB RAM) on a VM provisioned from Digital Ocean. The tests only utilize the most basic capabilities of the frameworks in question, therefore the main goal was to show the relative overhead these frameworks add to the handling of a request. This is not a test of the absolute performance as this will vary greatly depending on the environment and network conditions. This test also doesn’t cover the utility each framework provides and how this enables complex applications to be built with them. Continue reading

Design pattern of the day – Memento

Definition and use case from (https://dzone.com/refcardz/design-patterns)

Memento is a Behavioral Pattern( Used to manage algorithms, relationships, and responsibilities between objects ) .

Purpose
Allows for capturing and externalizing an object’s internal state so that it can be restored later, all without violating encapsulation. Continue reading

Understanding Xavier Initialization In Deep Neural Networks

I recently stumbled upon an interesting piece of information when I was working on deep neural networks. I started thinking about initialization of network weights and the theory behind it. Does the image to the left make sense now? The guy in that picture is lifting “weights” and we are talking about network “weights”. Anyway, when we implement convolutional neural networks, we tend to utilize all the knowledge and research available out there. A good number of things in deep learning are based on heuristics! It’s worth exploring why we do things in a certain way whenever it’s possible. This goes a long way in unlocking the hidden mysteries of deep learning and why it’s so unbelievably accurate. Let’s go ahead and understand how network weights are initialized, shall we? Continue reading