Stack Implementation in Java using Linked ListsTech by Sunny Srinidhi - December 31, 2019January 3, 20201 More in The Data Structures series. In our previous Stack implementation post, we saw how we can implement a Stack data structure using an ArrayList. But as you can imagine, that's not the right way to implement a stack. A much better implementation is using a LinkedList. In this post, we'll see just that. If you've missed it, I've already written about how to implement Single Linked List (SLL) and Double Linked List (DLL), and I'd encourage you to check those two out first as we'll be using the same Linked List implementation here, and you can find more detailed Linked List explanation there. Assuming that you have done that, let's now move on to the Stack. The Node The first thing we have
Double Linked List Implementation in JavaTech by Sunny Srinidhi - December 30, 20192 More in The Data Structures series. In the previous post, we saw how we can implement Single Linked List in Java. In this post, we'll see how we can extend that and implement a double linked list. The difference between a Single Linked List (SLL) and a Double Linked List (DLL) is that in DLL we have links to both the previous and the next node in the list. In SLL, we only have a pointer to the next node. So in DLL, we have the advantage of traversing the list in both the forward and reverse direction. This adds a lot more flexibility in the linked list. This ins't very much difficult once we have the SLL implementation done. So let's
Single Linked List Implementation in JavaTech by Sunny Srinidhi - December 23, 2019December 23, 20191 More in The Data Structures series. In the previous post, we saw how a stack can be implemented in Java. But as that was the first data structures post on this blog, I used an ArrayList internally. In this post, we'll implement a simple Linked List in Java. Starting with this post, we'll be getting serious about these data structure implementations. So we'll write 100% custom implementation without using any built-in classes in Java. Also, I'm not going to explain how the data structures work. Which means, in this post, I'll not have illustrations like I had for the stack implementation post explaining each step. So we're going to jump right into the implementation from now on. The Node We know that any linked
Stack Implementation example in JavaTech by Sunny Srinidhi - December 20, 2019December 23, 20192 More in The Data Structures series. A stack is one of the most simplest data structure to understand. If you had data structures in your academia, you already know what it means. It’s a simple Last In First Out (LIFO) queue. What that means is the last element to enter the stack will be first element to go out of the stack. Let’s try to understand the concept first with a few illustrations. The concept Suppose we have an empty container which looks like the container shown in the image below: Empty stack That’s pretty simple to understand. Now suppose again that we “push” a string with value “string1” to this empty stack. The stack now looks like this: Stack with one element That’s pretty simple to
Optimising a fastText model for better accuracyData Science by Sunny Srinidhi - December 3, 2019December 19, 20190 More in The fastText Series. In our previous post, we saw what n-grams are and how they are useful. Before that post, we built a simple text classifier using Facebook’s fastText library. In this post, we’ll see how we can optimise that model for better accuracy. Precision and Recall Precision and recall are two things we need to know to better understand the accuracy of our models. And these two things are not very difficult to understand. Precision is the number of correct labels that were predicted by the fastText model, and recall is the number of labels, out of the correct labels, that were successfully predicted. That might be a bit confusing, so let’s look at an example to understand it better. Suppose for a sentence
Understanding Word N-grams and N-gram Probability in Natural Language ProcessingData Science by Sunny Srinidhi - November 26, 2019December 19, 20192 More in The fastText Series. N-gram is probably the easiest concept to understand in the whole machine learning space, I guess. An N-gram means a sequence of N words. So for example, “Medium blog” is a 2-gram (a bigram), “A Medium blog post” is a 4-gram, and “Write on Medium” is a 3-gram (trigram). Well, that wasn’t very interesting or exciting. True, but we still have to look at the probability used with n-grams, which is quite interesting. Why N-gram though? Before we move on to the probability stuff, let’s answer this question first. Why is it that we need to learn n-gram and the related probability? Well, in Natural Language Processing, or NLP for short, n-grams are used for a variety of things.
An intro to text classification with Facebook’s fastText (Natural Language Processing)Data Science by Sunny Srinidhi - November 25, 2019December 19, 20193 More in The fastText Series. Text classification is a pretty common application of machine learning. In such an application, machine learning is used to categorise a piece of text into two or more categories. There are both supervised and unsupervised learning models for text classification. In this post, we’ll see how we can use Facebook’s fastText library for some simple text classification. fastText, developed by Facebook, is a popular library for text classification. The library is an open source project on GitHub, and is pretty active. The library also provides pre-built models for text classification, both supervised and unsupervised. In this post, we’ll check out how we can train the supervised model in the library for some quick text classification. The library
Data Science vs. Artificial Intelligence vs. Machine Learning vs. Deep LearningData Science by Sunny Srinidhi - November 18, 2019December 19, 20190 It’s very common these days to come across these terms - data science, artificial intelligence, machine learning, deep learning, neural networks, and much more. But what do these buzzwords actually mean? And why should you care about one or the other? I’m trying to answer these questions in this post, to the best of my capacity. But then again, I’m no expert here. This is the knowledge I’ve gained in the last few years of my data science and machine learning journey. I’m sure most of you will have better and easier ways of explaining things than I do, so I’ll be looking forward to reading your comments down below. Let’s get started then. Data Science Data science is all about data,
Top Five Machine Learning courses for beginners on UdemyData Science by Sunny Srinidhi - November 18, 2019December 19, 20192 Everybody wants to do machine learning these days. Machine learning, data science, artificial intelligence, deep learning, neural network — these have become some of the most used phrases in the tech space today. I’m not saying it’s particularly bad, but it definitely gets scary for somebody who doesn’t really know what all this means but wants to get into the rat race. When you think about it, from a software developer’s point of view, these are just different types of software or applications you work on, but with more math involved. I know I’m oversimplifying what data science is, but for somebody who doesn’t have a mathematics or statistics background, it is very difficult to understand the jargon initially. I’ve been there,
Getting started with Chalice to create AWS Lambdas in Python – Step by Step TutorialTech by Sunny Srinidhi - November 14, 2019November 14, 20190 If you’re into serverless stuff, you already know what is AWS Lambda. But if you don’t know, AWS Lambda is a serverless service provided by Amazon where you can create ‘functions’ and deploy them in AWS, which you can run without having any server instances (such as EC2). Read more... “Getting started with Chalice to create AWS Lambdas in Python – Step by Step Tutorial”