Comparing Neural Network Architectures
Last Updated on July 25, 2023 by Editorial Team
Author(s): Yan Gobeil
Originally published on Towards AI.
Comparing NN architectures through a language classifier, using Google Colab

After reading François Chollet’s wonderful book Deep Learning with Python I became curious about the different neural network architectures and which one is the best for various tasks. I had already thought of getting some practice with word data so I decided to take on the project of classifying the language that a word is written in. The first direction that I think of when working with words is to use recurrent neural networks. Chollet’s book also suggests that a series of 1D convolutions could be appropriate. Finally, I found a nice blog post that achieved a similar task using… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.