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Aakash Sharan

Agentic AI. Retrieval. Distributed Systems.

  • About
Aakash Sharan
Agentic AI. Retrieval. Distributed Systems.
  • Software Engineering

    A Guide to Understanding Order of Growth

    ByAakash Sharan January 10, 2018May 7, 2023

    Psst, hey you. Yeah, you. Have you seen this chart? Every software engineer worth their salt should remember this bad boy. It’s all about Big O concepts, which are super important, especially when designing APIs. That’s it. That’s the tweet. But seriously, Big O notation is key for understanding how algorithms scale and how much…

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  • Javascript | Programming

    Simplifying Javascript Techniques: A Guide to the Power of Hoisting

    ByAakash Sharan January 5, 2018May 7, 2023

    Hoisting is a funky Javascript mechanism where variables and functions get moved around like they’re playing a game of musical chairs. Here’s the deal: Only declarations get hoisted. Assignments or other executable logic are left in place, just like your friend who always bails on moving day. Functions get hoisted first and then variables, kind…

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  • Artificial Intelligence

    Optimizing Your Search Algorithms: Notes on Quiescent Search and Branching Factor

    ByAakash Sharan November 13, 2017May 7, 2023

    Branching Factor The branching factor is the number of children at each node. The effective branching factor is the number of children generated by a "typical" node for a given search problem. Quiescent Search A full-width search sees everything up to its horizon, and nothing beyond. This is called the horizon effect. It’s like not…

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  • Artificial Intelligence

    Mastering Search Optimization: An Introduction to Iterative Deepening

    ByAakash Sharan November 10, 2017May 7, 2023

    Depth-First Search (DFS) In DFS, we start from a node and go down a path until we reach a node that has no children. Whenever we run out of moves, we backtrack and explore the sibling of the node. And if there are no siblings, we go for the sibling of the grandparent and so…

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  • Artificial Intelligence

    Mastering AI: Enrolling in Udacity’s Artificial Intelligence Nanodegree

    ByAakash Sharan October 21, 2017May 7, 2023

    Let me tell you about my experience with creating an AI that plays Connect 4. I took an undergraduate CS course during my Masters and we created the AI using a few algorithms. To be honest, I don’t remember all of them, but I do recall using the min-max algorithm. The AI wasn’t too difficult…

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  • Blog

    Bridging the Gap Between Knowledge and Expertise: Professional Certification on Apache Cassandra

    ByAakash Sharan September 7, 2017May 7, 2023

    So I’ve been working with Apache Cassandra for over a year now and recently I decided to step up my game and get certified. And guess what? I passed Datastax’s Professional Certification on Apache Cassandra! The exam was purely theoretical, which means it didn’t ask me to calculate things like "partition size" and stuff. Datastax…

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  • Artificial Intelligence | Machine Learning

    Breaking Down the Beats: A Comprehensive Guide to Using ML Pipelines to Predict Song Release Years

    ByAakash Sharan December 1, 2016May 7, 2023

    Linear Regression is the most commonly used predictive analysis. It is used to model the relationship between a dependent variable and one or more independent variables. In this project we create an ML pipeline to train a linear regression model to predict the release year of a song given a set of audio features. We…

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  • Artificial Intelligence | Machine Learning

    Unlocking the Power of MapReduce: Using Python and Apache Spark for Enhanced Data Processing

    ByAakash Sharan November 26, 2016May 7, 2023

    Hey there! So we decided to create a Word Count application – a classic MapReduce example. But what the heck is a Word Count application, you ask? It’s basically a program that reads data and calculates the most common words. Easy peasy. For example: dataDF = sqlContext.createDataFrame([('Jax',), ('Rammus',), ('Zac',), ('Xin', ), ('Hecarim', ), ('Zac', ),…

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  • Data Engineering

    Data Wrangling Made Easy: Leveraging Apache Spark to Transform Raw Data into Valuable Insights

    ByAakash Sharan November 20, 2016May 7, 2023

    Hey, so I’m a big fan of Apache Spark and I’ve been using it for all of my independent projects. I recently had this idea to create a project that would showcase how to do some data wrangling with Apache Spark. For this project, we used Apache Spark 2.0.2 on Databricks cloud. Instead of using…

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  • Artificial Intelligence | Machine Learning

    The Art of Election Forecasting: Analyzing the 2012 US Presidential Election with Data Science

    ByAakash Sharan November 8, 2016May 7, 2023

    Hey there! Let’s talk about this dataset from RealClearPolitics and the US Presidential Election. Before we dive in, let’s get on the same page about a few things: The US Presidential Election happens every four years. There are 50 states in the US and each gets a certain number of electoral votes based on its…

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Recent Posts

  • What AI Exploit Benchmarks Actually Tell Us About System Architecture
  • The Hidden Architecture Behind Dense Vector Search (and Why It’s Hard to Scale)
  • The Hidden Complexity Behind Scaling Dense Vector Search
  • Distributed Vector Search: How Real Vector Databases Scale Beyond One Machine
  • The Write Path in Vector Databases (It’s a Distributed Systems Problem)

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