Installing Hadoop on the new M1 Pro and M1 Max MacBook ProData Science by Sunny Srinidhi - November 5, 2021November 5, 20213 We’ll see how to install and configure Hadoop and it’s components on MacOS running on the new M1 Pro and M1 Max chips by Apple.
Installing Hadoop on Windows 11 with WSL2Data Science by Sunny Srinidhi - November 1, 2021November 1, 20213 We’ll see how to install and configure Hadoop and it’s components on Windows 11 running a Linux distro using WSL 1 or 2.
Installing Zsh and Oh-my-zsh on Windows 11 with WSL2Tech by Sunny Srinidhi - October 27, 2021October 27, 20211 In this post, which is a part of a series of to setup Windows 11 and WSL2 for big data work, I install Zsh and Oh-my-zsh and setup up aliases
Getting Started With Apache AirflowData Science by Sunny Srinidhi - October 11, 2021October 11, 20210 I recently started working with Apache Airflow. And as is tradition, I’m telling you everything about it here.
Fake (almost) everything with FakerData Science by Sunny Srinidhi - September 30, 2021September 30, 20210 Generating customer and address data for testing has never been easier. We’ll see how to do that using the Faker Python library.
Querying Hive Tables From a Spring Boot AppData ScienceTech by Sunny Srinidhi - June 30, 2021June 30, 20211 In this post, we’ll see how to connect to a Hive database and run queries on that database from a Spring Boot application.
Getting Started With JanusGraphData Science by Sunny Srinidhi - February 25, 2021February 25, 20211 JanusGraph is a graph processing tool that can query distributed graph data in milliseconds. In this post, we’ll see how to get started with it.
Null Hypothesis and the P-ValueData Science by Sunny Srinidhi - November 8, 2019November 8, 20195 When you're starting your machine learning journey, you'll come across null hypothesis and the p-value. At a certain point in your journey, it becomes quite important to know what these mean to make meaningful decisions while designing your machine learning models. So in this post, I'll try to explain what these two things mean, and you try to understand that. Now, if you don't have a background in statistics, the definitions of null hypothesis and p-value will make no sense to you. It's just gibberish going way over your head. That's what happened to me the first few times I tried to understand them. It took me a good couple of days to get an idea of what they mean. I
Fit vs. Transform in SciKit libraries for Machine LearningData Science by Sunny Srinidhi - November 7, 2019November 7, 20190 We have seen methods such as fit(), transform(), and fit_transform() in a lot of SciKit's libraries. And almost all tutorials, including the ones I've written, only tell you to just use one of these methods. The obvious question that arises here is, what do those methods mean? What do you mean by fit something and transform something? The transform() method makes some sense, it just transforms the data, but what about fit()? In this post, we'll try to understand the difference between the two. To better understand the meaning of these methods, we'll take the Imputer class as an example, because the Imputer class has these methods. But before we get started, keep in mind that fitting something like an imputer
Apache Kafka Streams and Tables, the stream-table dualityData ScienceTech by Sunny Srinidhi - October 1, 2019February 25, 20200 In the previous post, we tried to understand the basics of Apache's Kafka Streams. In this post, we'll build on that knowledge and see how Kafka Streams can be used both as streams and tables. Stream processing has become very common in most modern applications today. You'll have a minimum of one stream coming into your system to be processed. And depending on your application, it'll mostly be stateless. But that's not the case with all applications. We'll have some sort of data enrichment going on in between streams. Suppose you have one stream of user activity coming in. You'll ideally have a user ID attached to each fact in that stream. But down the pipeline, user ID is