Day 27 : 'R' Programming
Meta Description: A beginner friendly introduction to R programming for data science. Learn R syntax, data types, vectors, data frames, and operators with simple examples and expected outputs. Introdu
Honors of AI/ML/DS
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Day 22 : Hadoop Architecture : HDFS, MapReduce and YARN
Finally, we get to know about Hadoop, exciting ain’t it? In the previous post, we learnt about the foundations of Big Data. To handle this Big Data we need an eco-system, and that eco-system is Hadoop
Day 21 : Introduction to the Big Data Ecosystem
Everyone uses YouTube. Every day there are millions of uploads (could be videos or shorts) on this popular video streaming channel. On top of that billions of people like, comment and share videos globally. These actions generate data, basically a di...
Day 20 : Neural Networks Basics (Perceptron, Forward & Backpropagation intro)
Imagine that you are walking down on a road and you see a pet dog. Now you don’t have a neuron by the name of “dog neuron“ which classifies the animal in front of me as dogs, right? Instead your brain activates many neurons at once, out of these, soe...
Day 19: Principal Component Analysis (PCA)
"Finding the most important story in a mountain of data"
Day 18: Hierarchical Clustering – Building a Family Tree for Data
Imagine you’re at a wedding. You don’t know many people there, so you start talking to the person closest to you. You realize you both love cricket, instant connection! A bit later, you and your new friend meet another person who also loves cricket, ...
Day 17: K-Means Clustering – Discovering Hidden Groups in Data
K-Means is one of the simplest and most popular clustering algorithms.It finds groups in your data, and every point belongs to one of these groups (called clusters). Before we dive into K-Means, let's first set the stage. In supervised learning, you ...