keras

Prototype and train neural networks using high-level Keras APIs.

1|Updated Jun 4, 2026
One-click install
npx skills add https://github.com/hung-phan/ml-skills --skill keras
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: keras
Source: https://github.com/hung-phan/ml-skills/tree/main/skills/ml-review/references/ml-libraries/keras
Command: npx skills add https://github.com/hung-phan/ml-skills --skill keras

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires keras, tensorflow, jax, torch, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill empowers rapid prototyping of neural networks using Keras, simplifying complex architectures without boilerplate code and providing flexible backend options.

Core Features & Use Cases

  • High-level API: Simplify neural network construction using Sequential and Functional APIs.
  • Transfer Learning: Quickly adapt existing models to new tasks with minimal code.
  • Backends: Run on TensorFlow, JAX, or PyTorch with the same model definition, enabling cross-backend portability.
  • Use Case: When building a simple image classification model for a rapid prototype or a transfer learning experiment, Keras makes it possible to define and train the model in minutes.

Quick Start

Construct a Sequential model with Keras to classify images.

Frequently Asked Questions about keras

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I prototype a neural network without writing boilerplate code?

You can prototype a neural network using high-level Keras APIs like Sequential and Functional models to simplify complex architectures without boilerplate code, enabling rapid development of standard architectures in minutes.

Can I use the same Keras model definition across TensorFlow, JAX, and PyTorch?

Yes, the same Keras model definition can run on TensorFlow, JAX, or PyTorch backends, enabling cross-backend portability and simplifying the transition between different deep learning frameworks.

What is the best way to adapt an existing model to a new task?

The best way to adapt an existing model to a new task is using Keras transfer learning, which allows you to quickly adapt pre-trained neural networks to new tasks with minimal code adjustments.

Do I need prior knowledge of Keras to build an image classification model?

Yes, you need prior knowledge of Keras and a defined neural network model to train. This Skill provides high-level APIs for rapid prototyping but requires understanding of deep learning concepts.