A good system needs to make sure that race condition and deadlock can’t occur. In this post, let us learn about Race Condition and Deadlock.Continue reading “Race Condition and Deadlock”
There are many Big Data Solution stacks.
The first and most powerful stack is Apache Hadoop and Spark together. While Hadoop provides storage for structured and unstructured data, Spark provides the computational capability on top of Hadoop.Continue reading “Understanding Big Data Stack – Apache Hadoop and Spark”
As everyone knows, Big Data is a term of fascination in the present-day era of computing. It is in high demand in today’s IT industry and is believed to revolutionize technical solutions like never before.Continue reading “Introduction to Big Data and Distributed Systems”
It is a well-known fact that deep learning models are heavy; with a lot of weights for the deep layers. And it is obviously an overhead to load the model every time we need to get the predictions from the model. Thus this is costly in terms of the time of execution.
In this project, we will mainly focus on addressing this issue, by uniquely integrating the networking functionalities provided by ZMQ library. We will build a server-client based architecture to make the model load exactly once(that is during the starting of the app). The predictions from the model will be served by the model server, as long as it listens to its Flask client which requests it for the predictions for an input image.Continue reading “Improving the Performance of Deep-Learning based Flask App with ZMQ”