Let's learn about Data Structures via these 123 free blog posts. They are ordered by HackerNoon reader engagement data. Visit the Learn Repo or LearnRepo.com to find the most read blog posts about any technology.
Data structures are fundamental ways of organizing and storing data in a computer, such as arrays, linked lists, and trees. They are crucial because efficient data structures optimize algorithm performance, enabling faster and more scalable software development.
1. Top 10 System Design Interview Questions for Software Engineers
2. Java Algorithms: Merge k Sorted Lists (LeetCode)
An easy approach to the hard leetcode problem Merge k Sorted Lists from that many people using Java Algorithms will need to learn in order to be effective.
3. How to Implement Trie (Prefix Tree) - Blind 75 LeetCode Questions
A trie (pronounced as “try”) or prefix tree is a tree data structure used to efficiently store and retrieve keys in a dataset of strings.
4. How To Merge Two Sorted Lists
We can use LinkedList to merge both sorted lists, though there are considerations to doing it single or double-linked that may complicate the operation.
5. Java Algorithms: Coding a Binary Tree Right Side View (LeetCode)
In this article, you will learn how to code a Binary Tree Right side view in LeetCode.
6. How to Solve Number of Islands From Blind 75 LeetCode Questions
We will learn how to solve "Number of Islands" from Blind 75 LeetCode Questions.
7. Clone Graph Blind75 LeetCode Problem
Clone Graph Blind75 LeetCode Problem
8. Merge Intervals in Java Algorithms (LeetCode)
Returning an array of the non-overlapping intervals that span every input interval.
9. Validate Binary Search Tree Blind 75 LeetCode Question
Given the root of a binary tree, determine if it is a valid binary search tree (BST
10. Space and Time Receives $20 Million in Strategic Investment Led by Microsoft's M12
Space and Time, a Web3 native data platform that has raised $20 million in strategic capital from notable investors led by Microsoft's M12 fund.
11. The Algorithm for Inserting Sequences into Sequences
Insert ordered sequences with a string-based algorithm that avoids recalculations, perfect for large datasets in product lists, chats, or task management.
12. Comparing Coding Platforms: LeetCode, CodeWars, CodeSignal, and HackerRank
Exploring coding platforms: My insights and experiences shared. Discover the pros and cons of informed choices. Join me on this insightful journey!
13. Optimizing List Manipulation: Two Pointers Technique
"Optimizing List Manipulation: Two Pointers Technique" explores the effective application of the two-pointer technique to efficiently manipulate lists, reducing
14. Understanding the Sliding Window Pattern: Efficient Utilization Through Examples
The article explores the Sliding Window pattern's efficient application through illustrative examples.
15. Manacher’s Algorithm Explained— Longest Palindromic Substring
Manacher’s Algorithm helps us find the longest palindromic substring in the given string. It optimizes over the brute force solution by using some insights into how palindromes work. How? Let’s see!
16. Rusty Chains: A Basic Blockchain Implementation Written in Pure Rust
A hands-on tutorial on blockchain basics, taxonomy and Rust.
17. Java Algorithms: First Missing Positive (LeetCode)
The First Missing Positive problem is an algorithm problem that requires finding the smallest positive integer that is not present in a given unsorted array of
18. Hadoop Across Multiple Data Centers
Hadoop cluster across multiple data centers
19. Top 3 Coding Challenges for Mid-level JavaScript developers
If you have a considerable amount of experience with JavaScript, you are expected to solve complex coding challenges.
20. 7 Essential Tips for Competitive Programming and DSA
I had to quit DSA and CP within a month because of the overwhelming exhaustion, This blog discusses mistakes that I made while learning DSA and CP.
21. An Intro to Algorithms and Data Structures (Javascript Edition)
Understanding algorithms and data structures are crucial to enhancing your performance 10x more than your peers who don't. This is because you analyze problems.
22. Creating a C++ Program To Do Binary Subtraction
Understand how to do binary subtraction in data structures. Binary subtraction is one of the four arithmetic operations where we perform the subtraction method.
23. Here's How to Learn Data Structures the Fun Way With Flutter
Inspired by Google’s Applied CS with Android, this adaptation for Flutter provides an interactive way to understand Arrays, HashSets, and HashMaps.
24. The Big O Notation in JavaScript
Understanding the Bachmann-Landau notation
25. Mastering Maps in Go: Everything You Need to Know
Learn about using maps in Go (golang), including associative arrays, hash maps, collision handling, and sync.Map, with practical code examples.
26. Empowering Newbies: Building Confidence Through 600+ LeetCode Solutions – A Guide for Beginners
Discover valuable insights on tackling over 600 LeetCode problems. Gain practical advice and useful resources for mastering coding interviews successfully.
27. The ATM Problem: Why the Greedy Algorithm Isn't an Optimal Solution
Solution to a popular Interview problem: Solve ATM task with Greedy Algorithm
28. Linked List Implementation With Examples and Animation
A linked list is one of the most basic data structures in computer science. In this article, we will go through the following topics:
29. How to Solve "Struct Containing a (Nested) Mapping Cannot be Constructed" in Solidity
How to Solve "Struct Containing a (Nested) Mapping Cannot be Constructed" in Solidity
30. Filtering Dictionary In Python 3
Originally published on melvinkoh.me
31. 30 Days DSA Interview Preparation Plan
All data structures and algorithms concepts and solutions to various problems in Python3 stored in a structured manner to prepare for coding interviews.
32. How to Remove Duplicates in Go Slices
Different ways to remove duplicates in slices in Go, a powerful language whose lack of tools makes learning this necessary if you want to make full use of it.
33. 5 Steps to Improve Your Data Structure and Algorithm Skills
Learn 5 steps to Improve DSA skills. Data structure and algorithms are the most important skills to be prepared for an interview at a top product-based company
34. How to Write Smart Contracts for Merkle Tree Using Solidity
A Merkle tree is a data structure hierarchy used to verify if a particular data is part of a dataset without expending too many resources.
35. How I got a Job at Facebook as a Machine Learning Engineer
It was August last year and I was in the process of giving interviews. By that point in time, I was already interviewing for Google India and Amazon India for Machine Learning and Data Science roles respectively. And then my senior advised me to apply for a role in Facebook London.
36. Algorithms and Data Structures
Well, this is where you are separated by the ones who are good or excellent software developers. In this case, I will tell you that at the beginning or at least in my case and I know that most of the time and for most people who I know, you will feel like an incompetent or an idiot. Basically, how is it possible that I cannot understand this and then you get frustrated.
37. Graph Representation in C++ (Job Interview Cheatsheet)
Update: you can watch a video on Graph Representation in C++ here:
38. Kth Largest Element in an Array - Quickselect Using Lomuto Partitioning Scheme.
Solving k-th largest element in the array using heap and quickselect
39. The Ultimate Strategy to Preparing for the Coding Interview
How to do faster preparation for coding interviews?
40. How to Prepare Yourself For Data Structures and Algorithms Interviews at FAANG
Written By Esco Obong (@escobyte on Twitter), Senior Software Engineer @Uber, Founder of Algorythm study group on Facebook and Black Software Engineers Career Support Group on LinkedIn.
41. Prefix Sums and How They Can be Used to Solve Coding Problems
In this post, we will look at prefix sums and how they can be used to solve a common coding problem, that is, calculating the sum of an array (segment). This article will use Java for the code samples but the concept should apply to most programming languages.
42. Build an Array from Scratch in Javascript
In the last post Arrays in JS, we learned about what arrays are, how we can store data in them and some methods which can be used on the array to get certain results.
43. How to use Redis HyperLogLog
How to use Redis HyperLogLog data structure to store millions of unique items.
44. BFS, DFS, Dijkstra, and A-Star Are Basically the Same Algorithm, I'll Show You Why
It turns out that well-known algorithms like BFS, DFS, Dijkstra, and A-Star are essentially variations of the same universal algorithm.
45. How To Search An Element In Sorted Matrix In Linear Time
Statement
46. The Ultimate Guide to Data Structures & Algorithms for Beginners
The need of the hour, especially in the corporate world, is to find professionals who have sufficient knowledge about data structures and algorithms.
47. Probabilistic Data Structures And Algorithms In Big Data
Probabilistic data structures allow you to conquer the beast and give you an estimated view of some data characteristics
48. Multiply Strings (LeetCode): An Out of the Box Solution In JavaScript
Given two non-negative integers num1 and num2 represented as strings, return the product of num1 and num2, also represented as a string.
49. A Comprehensive Guide for Building Efficient Data Structures in Dart
The most important Data structures explained in code for cracking the coding interview. Understand and learn how to implement them. Crack the interview
50. Data Gathering Methods: How to Crawl, Scrape, and Parse Data Online
The internet is a treasure trove of valuable information. Read this article to find out how web crawling, scraping, and parsing can help you.
51. 9 Best Data Integration Software in 2022
52. The Future of the Internet Through the Web 3.0 Lens
Jules Verne, John Brunner, Arthur Clarke, William Gibson, George Orwell — it’s a short list of writers who predicted the future in their books. They’ve written about social and technical changes that will take place in human society. Here we are, facing those changes good or bad.
53. Bloom Filter Basics in Go
Learn about Bloom filters: memory-efficient data structures using hashing for fast set membership queries.
54. Augmented Linked Lists: An Essential Guide
While a linked list is primarily a write-only and sequence-scanning data structure, it can be optimized in different ways.
55. 5 Books You Can Read to Boost Your Computer Science Knowledge
Make use of your downtime and read something good!
56. Lists in Python: Mutability, Utility, and Accessibility
A list is a sequence in python. The dictionary meaning of list is “a number of connected items or names written or printed consecutively”. There is no much difference in its dictionary meaning and its uses in Python while writing a program.
57. 4 Tips To Become A Successful Entry-Level Data Analyst
Companies across every industry rely on big data to make strategic decisions about their business, which is why data analyst roles are constantly in demand.
58. Blockchain: What the Hell is a Merkle Tree?
59. Merging Datasets from Different Timescales
One of the trickiest situations in machine learning is when you have to deal with datasets coming from different time scales.
60. Visualizing the Beap: A Lesser-Known but Fascinating Heap Variant
Beap is designed to make both insertion and search operations efficient, giving us O(√n) time complexity for both.
61. Understanding LinkedList Data Structure in Ruby
If you are familiar with data structures you may have heard about a LinkedList.
62. Foursquare Enters the Future With a Geospatial Knowledge Graph
Foursquare is evolving, and its next steps will be powered by the Foursquare Graph
63. Prepare For Your Next Tech Interview With These 17 Data Structures and Algorithms Sites
I've compiled some of the most useful resources for DSAs, interview practice sites, commonly asked technical questions, and sites to build practical projects.
64. Why Your Business Requires Data Driven Growth-Marketing?
Need rapid surge in digital marketing? Entrepreneur and agile startups can now easily reach their target audience due to data driven growth-marketing analytics.
65. The Anatomy of a Real-Time Video Recommendation System
Learn the key stages of implementation, the role of tools like FastAPI, and the significance of algorithms like ANNs in creating personalized experiences.
66. Useful Resources for Data Structure & Algorithm Practice
These four resources may be useful for learning about data structures and practicing making algorithms for your advanced programming needs in your work.
67. Different Types of Graphs in Data Structure
Learn about different types of graphs in the data structure. Graphs in the data structure can be of various types, read this article to know more.
68. Data Structures and Algorithms: How I Failed a Google Interview
Learn about why data structures and algorithms are important, and why I failed a Google interview.
69. A High Level Explanation of Data Types for Decision Makers
There are three different types of data: structured data, semi structured data, and unstructured data.
70. Exploring the CAP Theorem: The Ultimate Battle of Trade-Offs in Distributed Systems
Consistency, availability, and partition tolerance are the three musketeers of distributed systems. They ensure that your system operates correctly.
71. Convert Formatted Text Into a Data Structure Using Parsing
Parsing is a process of converting formatted text into a data structure. A data structure type can be any suitable representation of the information engraved in the source text.
72. How to Implement Heap in Data Structure
Heap data structure is a balanced binary tree data structure where the child node is placed in comparison to the root node and then arranged accordingly.
73. How A Database Get Rid of OOM Crashes
What guarantees system stability in large data query tasks? It is an effective memory allocation and monitoring mechanism.
74. Go: When Should You Use Generics? When Shouldn't You?
I’ll provide general guidelines, not hard and fast rules. Use your own judgement. But if you aren’t sure, I recommend using the guidelines shown here.
75. 87 Stories To Learn About Data Structures
Learn everything you need to know about Data Structures via these 87 free HackerNoon stories.
76. Stacks in Programming: Understanding the LIFO Data Structure and Its Applications
Explore the concept of stacks in programming, their applications, speed, and the origin of "Stack Overflow."
77. CS Data Structures: Fixed Array
A fixed array is an array that has a max amount of items. Such arrays are used when the programmer knows how many elements an array should hold.
78. Master Dynamic Data with Solidity Linked Lists
Unlock the secrets of efficient data handling in Solidity with Linked Lists. Dive in now to elevate your blockchain development game.
79. Hierarchical Queries: Comparative Analysis in Oracle and PostgreSQL
A guide about hierarchical querying in Oracle & PostgreSQL, comparing syntax, efficiency, & suitability for diverse data structures.
80. Understanding the Main Differences between Structured and Unstructured Data
In this, I explore structured, unstructured, and semi-structured data, as well as how to convert unstructured data, and AI’s impact on data management.
81. Mastering Hashing in Java: A Comprehensive Guide to HashMap and HashSet
82. Understanding Bloom Filters: An Efficient Probabilistic Data Structure
Learn about bloom filters, pros/cons and their applications.
83. The Anatomy of a Write Operation
When file.write() returns, your data isn't on disk. Trace the 6-layer journey of a write operation from Python buffers to Linux kernel and SSD silicon.
84. What Is the Use of a Linked List Class?
Whether you're a beginner programmer or an experienced developer, understanding the linked list class is essential.
85. Poor Data Quality is the Bane of Machine Learning Models
An examination of the importance of data quality, how it can present itself in a dataset, and how it can impact machine learning models.
86. How to Optimize Tree Recursion in JavaScript
Learn how tree recursion works in JavaScript, the risks of stack overflows, and how to optimize traversal using tail-recursive and iterative methods.
87. Data Quality: Its Definitions And How to Improve It
Utilizing quality data is essential for business operations. This article explores data quality definitions and how to maintain it for everyday use.
88. The Biggest Features in ES2020/ES2021
ES2020/ES2021, New ES2020/ES2021 features you might have missed
89. 4 Ways Data Science Helps Streamline Business Operations
Data Science has changed the way organizations collect, analyze, and process different types of information.
90. How to Check If Your Point Is Reachable: A JavaScript Algorithms Guide
91. Discover Funnel Bottlenecks: Step-by-Step Analysis with BigQuery
Learn how to use BigQuery for e-commerce funnel analysis. Track user transitions between steps like “add to cart” and “purchase,” and identify where to improve
92. The Pain Points of Scaling Data Science
While building a machine learning model, data scaling in machine learning is the most significant element through data pre-processing. Scaling may recognize the difference between a model of poor machine learning and a stronger one.
93. CPython Lists, Explained Like You’re the Interpreter
A practical deep dive into how list works in CPython: why indexing is fast, what size vs capacity really means, and why append() is amortized O(1).
94. How Companies like Netflix Deliver Content Around the World
Have you ever wondered how companies like Netflix or Spotify is able to delivery videos or songs to you at what seems like lightning fast speed !?
95. What Are Conflict-free Replicated Data Types (CRDTs)?
In a world where most of the apps that we use on the internet are collaborative in nature, conflicts in data are common. Is there a way to avoid it?
96. How to Build a Versatile Traverse Function from Scratch
Learn how to create your own traverse function in under 5 minutes.
97. A Complete Introduction to Graph Data Structure
Data structures are important for storing data in efficient ways. In this article, we will discuss the Graph Data Structure: definition, types and examples.
98. Watch Out for Deceitful Data
Nowadays, most assertions need to be backed with data, as such, it is not uncommon to encounter data that has been manipulated in some way to validate a story.
99. DeFi Meets NFT With $MEGA Yield Farming in The MCP3D Decentralized City
Recent months demonstrated explosive growth of Decentralized Finance with $13B+ in total value locked. Normally, games are the first thing to take off on new platforms, and seems like DeFi is not an exception here.
100. Fundamentals of Data Structures [Part 1]
A trip down memory lane avid reader. Let's take a walk through the core of it all: data structures. What are they and why are they so important? A 'hello' to a reader that might have missed our talk on Memory management, where we delved into what happens to our code in variable assignment. Do take a look, even if it's a refresher you're looking for.
101. Data Speedways: How Kafka Races Ahead in System Design
Unlock the Power of Real-Time Data with Kafka: A Deep Dive into the Fast and Scalable System Design Championed by Kafka. Learn More!
102. The Guide To Lisk Tree with Use Cases
If you are interested in blockchains and cryptocurrencies, it is likely that you may have stumbled across Merkle trees (also known as hash trees).
103. Who Doesn't Love the Classic Snake Game?
Create a classic Snake game using Python and Pygame. Learn game development basics, including loops, conditionals, and rendering graphics.
104. From Data Mess to Data Mesh: How to Optimize Business Intelligence
Digitization as a trend means the world is now generating more data than ever before. How said data is managed is crucial for business and individuals alike.
105. The Noonification: Augmented Linked Lists: An Essential Guide (8/2/2024)
8/2/2024: Top 5 stories on the HackerNoon homepage!
106. An Introduction to Data Automation for Business Efficiency
In today’s competitive business landscape, data automation has become necessary for business sustainability. Despite the necessity, it also comes with a few challenges--collecting, cleaning, andputting it together--to get meaningful insights.
107. Applying Criminology Theories to Data Management: "The Broken Window Theory: and "The Perfect Storm"
What can be done to prevent “Broken Windows” in the primary data source? How can we effectively fix existing “Broken Windows"?
108. Augmented Tree Data Structures
Data structures are a serious tool to store data conveniently. Modern applications have the flexibility to organize the data in the memory or on disk using vari
109. Build Resilient Data Pipelines by Empowering Non-Technical Teams to Detect and Resolve Bad Data
Streamline your data pipeline by enabling non-engineers to define validation logic, review data, and fix issues.
110. Decoding Database Complexity: A Journey from Text Files to LSM Trees and B-Trees
Dive into the intricacies of databases, starting from the simplest key-value store using bash functions to the complexities of LSM trees and B-trees.
111. The Missing Link: Why Are Linked Lists Useful in Software?
I like to start off Metaphysically then move down into the specifics of something. So then why are Linked Lists useful in software? Well I’ll answer with the question “Why have belongings if you have no place to store them?”; What good are your belongings if you cannot keep them anywhere?
112. The 5 Ingenious Data Structures (and What They Actually Do)
Explore 5 advanced data structures that go beyond arrays and linked lists. Learn how B-Trees, Bloom Filters, Radix Trees, and more power modern systems.
113. Where Visuals And Algorithms Collide: How Unrelated Algorithms Produce Intuitive Markings
A nautilus seashell with a perfect spiral is the product of specific DNA that coded for its existence.
114. Data Storage Security: 5 Best Practices to Secure Your Data
115. Syncing Data from Coda to Google Sheets And Vice Versa with Google Apps Script [A How-To Guide]
Last year I published a tutorial on how to sync data between two Coda docs and data between two Google Sheets. What was missing from the tutorial was how to sync data between a Coda doc and a Google Sheet.
116. Data Backup Strategy To Reduce Data Loss
Backing up the data is one of the most important processes for businesses. It requires creating a copy of all your data and storing it.
117. Let’s Have a Talk About Go Slices
Today we will discover Slices, one of the core data structures in Go.
118. Bloom Filters - Power in Simplicity
Short article about bloom filters
119. How to Get Faster Go Maps Using Swiss Tables
In this blog post, we’ll look at how Swiss Tables improve upon traditional hash tables
120. A Node of Truth For Making Graphs
When you are learning software you will have to pick and choose what. There is just too much to learn it all. So much is really cool and fulfilling but some of it is more tedious and feels like busy work. However there are things you will have to know; the fundamentals are a requirement no matter what you choose. Whether its Machine Learning and Neural Networks or Web Development and REST APIs you will need to know the fundamentals for both.
121. Are MySQL replications as smooth as you think they are?
What are you actually missing out on in MySQL replication? It appears easy, but to debug the problem caused by it takes a lot of time. So, here's your answer.
122. The “Grind LeetCode” Advice is Mathematically Stupid (I Scraped 1,500 Questions to Prove It)
I scraped 1500+ tech interview questions to expose company biases. Stop paying $35/mo for LeetCode Premium. Search your target company's exact data for free.
123. What is a Lisk Tree and What are its Use Cases?
If you are interested in blockchains and cryptocurrencies, it is likely that you may have stumbled across Merkle trees (also known as hash trees).
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