Wow, it’s been such a long time since I made a post here. I’ve been working hard, learning a lot, and I’m pleased to share that I have made sizeable strides into the world of Data Science!
Since I’ve been gone, I saw that according to my post statistics I have totaled over 100k views! That’s so amazing. Speaking of statistics, they have been on my mind for the past year! You might be wondering though, why? Well, statistics is truly the heart of the scientific method, and plays an integral role in Artificial Intelligence, Machine Learning and Data Science.
Today I’ll be starting a new series called “Data Science Zero to Hero” where I will be breaking down popular concepts so that those who are interested in learning about ML, AI and data science can learn in a guided way without any prior knowledge. It’s also worth noting that these terms are often used interchangeably, but are not necessarily the same things.
Artificial Intelligence (AI) is a broad concept focused on creating machines that can mimic human thinking, reasoning, and behavior. On the other hand, Machine Learning (ML) is a subset of AI where computer systems learn from their environment, using these learnings to enhance experiences and processes. It’s important to note that all ML is AI, but not all AI involves ML.
Data Science, in contrast, involves processing, analyzing, and extracting relevant insights from data. Data Scientists utilize machine learning techniques to predict future events by uncovering hidden patterns in the data.
A little bit about myself…
Just a little bit of background into what I learned so far - I took MIT’s online Applied Data Science course and learned tons. If anyone is interested in an introduction to learning Data Science, I would definitely recommend it.
My goal is to learn by teaching, and to help those who are intimidated by complex technical concepts. I hope that you’re as excited as I am! Thanks for reading!