Here I am writing my first post, I posponed it for a long time… In this article I would like to share my experience installing and testing basic Apache Kafka features. If you are new in the Big Data ecosystem let me give you some short concepts.
In this tutorial, we are going to use the K-Nearest Neighbors (KNN) algorithm to solve a classification problem. Firstly, what exactly do we mean by classification?
A complete walk through using Bayesian optimization for automated hyperparameter tuning in Python
RStudio version 1.1 introduced the Terminal functionality, which does not seem to be getting enough deserved attention and love even though it is very well integrated with the rest of the IDE and can be extremely useful for several daily use-cases. In short, the RStudio Terminal provides access to the system shell directly from the RStudio IDE, supporting xterm emulation, full-screen terminal applications, command line operations and more. It also has useful customizable keyboard shortcut bindings to make frequent usage more efficient and enables usage of multiple such Terminals simultaneously.
Everyone who has been working with distributed systems or logs from such a systems, has directly or indirectly encountered Lamport Timestamps. Lamport Timestamps are used to (partially) order events in a distributed system. The algorithm is based on causal ordening of events and is the foundation of more advanced clocks such as Vector Clocks and Interval Tree Clocks (ITC).