Machine Learning and More — A Catch-Up!

Hello, everyone!

Sidharta here! It has been a while since my last post and I have learned and done a lot since then! Allow me to share with you some of my machine learning exploits in the year of 2020 and what new content you can look forward to:

Nanodegree

As you may already know, if you have read some of my other blog posts, in the summer, I completed an Udacity nanodegree on AI Programming with Python, where I successfully built a neural network model that trained itself on a dataset of images of various animal and everyday items and could successfully classify new pictures of dogs into the correct dog breeds.

Course: CS4641, Georgia Tech

More recently, I have recently finished my second fall semester at the Georgia Institute of Technology (remotely, due to the COVID19 pandemic). One of the courses that I finished was CS4641, also called “Introduction to Machine Learning”. In this course, I learned the fundamentals of two main kinds of machine learning. There is unsupervised learning, where models learn to group unlabeled data (like K-means and density clustering), and then there is supervised learning, where models use past examples to classify or predict new results (like neural networks). Each kind of machine learning has several algorithms that help them perform there tasks in different ways.

I will be a Teaching Assistant for CS4641 in the Spring 2021 semester! The instructor I’ll be helping was someone who really encouraged my pursuits in the field, Prof. Mahdi Roozbahani. I can’t wait to get started!

Computer Vision Exploits

In addition to finishing CS4641, I have been looking into the applications of machine learning and artificial intelligence, one of the most famous of which is computer vision. The field focuses on the study of detection and manipulation of visual data.

My tool of choice for tackling this field so far has been OpenCV, a computer vision library that is Python-friendly. The library comes with a variety of tools, such as basic shape-drawing and color filters. However, its most famous assets are its database of models that help with facial recognition.

The YouTuber sentdex has a series where he shows how to use OpenCV, which has been very helpful in my practice with its tools. A link to the start of his series can be found here.

What Next

In the near future, I’ll be posting more content going more in depth with the subjects I have brought up in this post. For machine learning, not only will I demonstrate what I have learned, but also show some of my insights on the field, having experienced it from a few angles. Such insights might include the distinction and relationship between machine learning, computer vision, and artificial intelligence.

This content may take the form of videos or a new online course on the website.

Additionally, I will be creating new content for robotics and I will will be developing new DIY kits and materials for people to use as well, so stay tuned!

Be sure to look out for new updates and to follow GearsNGenes on Twitter, YouTube, and Facebook!

Thank you for reading the post! Until next time, keep building and stay creative!

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