Andrej Karpathy’s YouTube video course — Lecture Notes. Part 1.
This post is based entirely on Andrej Karpathy’s video tutorial “The spelled-out intro to neural networks” — https://www.youtube.com/watch?v=VMj-3S1tku0&t=4822s
In this post, we will learn about the very basic mechanisms of neural networks — how does a network learn to classify dog and cat images? How does a network... [Read More]
Hello readers,
In this article, we will dive deep into a new and exciting text-to-speech model developed by Microsoft Research, called VALL-E. The paper presenting the work has been released on Jan. 5, 2023, and since then has been gaining much attention online. It is worth noting that as of writing... [Read More]
Hi all,
I am sharing a short project I worked on that involves improving the performance of the text-davinci-003 model by OpenAI using intelligent prompting. I will start by saying that this work is inspired by the excellent video tutorials by James Briggs — (specifically this one — https://youtu.be/dRUIGgNBvVk) and much of the... [Read More]
In this article, I will present the topic of sentence embeddings. We will learn what sentence embeddings are and how they can be helpful. We will review some basic (and even naive) methods for creating sentence embeddings and also some recent advances in the field. We will end with an... [Read More]
In this article, I will share the process of creating my personal website and portfolio using Jekyll. Jekyll is a Ruby Gem used to easily create static websites whose content is predetermined at build time and not dependent on any live user input or database connection.
As I am... [Read More]
In this article, we are going to build together the classic game of Snake using Go. This is my first project in Go and what better opportunity to share my learning experience with you and hopefully help your journey to learning Go as well?
The full code for this project (separated into... [Read More]
Hello readers,
For those of you who haven’t read the previous part, here is the link:
MovieLens-1M Deep Dive — Part I
In that article, I present the MovieLens-1M [1] dataset (a movie recommendations dataset that contains 1 million ratings for movies made by different users) along with some exploratory data analysis and try out... [Read More]
Recommendations. We all consume them. Be it through our favorite movie streaming apps, online shopping, or even passively as a target of advertising campaigns. How are these recommendations created? How does a recommendation system utilize enormous datasets of internet transactions to generate high quality and personalized recommendations? I find these... [Read More]
Hi all,
This is a super-short weekend project. We are going to create a simple GUI application in python which highlights specific colors in an image and reports which percentage of the image was highlighted. Let’s show an example of the GUI:
Let’s start our project with some necessary imports:
Let’s create a MainWindow... [Read More]
Hello Medium. I have decided to pick up on the super-relevant subject of predictive maintenance and start with the industry gold standard — the NASA Turbofan Engine Degradation Simulation Data Set (https://ti.arc.nasa.gov/tech/dash/groups/pcoe/prognostic-data-repository/#turbofan).
My journey was highly influenced by Koen Peters’s awesome series regarding the analysis of this dataset and his... [Read More]