Neural Networks from Scratch with Python Code and Math in Detail— I
Last Updated on July 20, 2023 by Editorial Team
Author(s): Towards AI Editorial Team
Originally published on Towards AI.
Building neural networks from scratch. From the math behind them to step-by-step implementation coding samples in Python with Google Colab
Top highlight
Source: Pixabay
Author(s): Pratik Shukla, Roberto Iriondo
Last updated December 1, 2021
Join Towards AI, by becoming a member, you will not only be supporting Towards AI, but you will have access to…
members.towardsai.net
Note: In our second tutorial on neural networks, we dive in-depth into the limitations and advantages of using neural networks. We show how to implement neural nets with hidden layers and how these lead to a higher accuracy rate on our predictions, along with implementation samples in Python on Google Colab.
Figure 1: Where neural networks fit in AI, machine learning, and deep learning.
Neural networks form the base of deep learning,… 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.
Related posts
Recent Posts
