Sure, here’s the corrected and rewritten version of the text: Yo, listen up! When a function accepts another function as an argument, that contained function is called a callback function. Using callbacks is a core functional programming concept. It’s like calling your bestie to ask for help, and they call you back with a solution. […]
Step-by-Step Guide: Installing TensorFlow on Windows
Hey there! Want to install Tensorflow on your Windows machine? No worries, I’ve got you covered! Just follow the steps mentioned below. First things first, head over to the Anaconda website and install version 3.6. Once you’ve done that, open the terminal and check your python version by running python -V. It should print out […]
A Guide to Understanding Order of Growth
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 […]
Simplifying Javascript Techniques: A Guide to the Power of Hoisting
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 […]
Optimizing Your Search Algorithms: Notes on Quiescent Search and Branching Factor
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 […]
Mastering Search Optimization: An Introduction to Iterative Deepening
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 […]
Mastering AI: Enrolling in Udacity’s Artificial Intelligence Nanodegree
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 […]
Bridging the Gap Between Knowledge and Expertise: Professional Certification on Apache Cassandra
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 […]
Breaking Down the Beats: A Comprehensive Guide to Using ML Pipelines to Predict Song Release Years
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 […]
Unlocking the Power of MapReduce: Using Python and Apache Spark for Enhanced Data Processing
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', ), […]