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An interactive tool to visualize the training of neural networks. Explore how inputs and outputs are represented in a classifier, and see how hidden nodes and weights change over time. This neural network is a simple classifier. It takes 5x5 pixel images as input, and outputs the digit that each image represents. All 25 pixels of the image are fed into the neural network as input nodes. Hidden Neurons: Iterations: Reset ↺ Train → Iterations: 0 | Accuracy: 0% | Loss: N/A Things to Play With When you first load the page, the network weights are randomly initialized and no training has been done....

A simple 8 puzzle solver. (With your choice of heuristic function and search algorithm!) | I first wrote an 8 puzzle solver some years in my university Artificial Intelligence class. That version was a terminal program written in Python. Manhattan Distance Hamming Distance A-Star Search Breadth First Greedy Best First ◀ ▶...

FORTH is a simple stack-based language. It is a great language to learn about compilers and interpreters. This article will show you how to write a FORTH compiler and interpreter in 130* lines of Python. Get all the code on Github Introduction FORTH is a simple stack-based language. It is a great language to learn about compilers and interpreters. This article will show you how to write a FORTH compiler and interpreter in 130* lines of Python....

In mid 2021, there was lots of excitement around the flexibility of large transformer models. I wanted to see if I could use GPT-J as an all-in-one news-based trading bot. The idea being, if the model has read enough of the internet as background, it should understand the context of a news article, and output a trading signal for a given company. Read the full paper PDF. Background Back in the dark ages (yes, I mean before Chat-GPT took the internet by storm), transformer-based text generation models were known only to AI researchers and the nerdiest of programmers....