Written by experts in AI, machine learning, and deep learning, the Hands-On AI tutorial series covers the tools, infrastructure, and techniques to help you build an application with powerful AI capabilities.
- Docker* containers
- Keras neural network API
- TensorFlow* software library for machine intelligence
- Caffe* deep learning framework
- Intermediate knowledge of Python*
- Basic linear algebra
- Basic statistics
- Basic probability theory
- Familiarity with GitHub*
Anyone can follow along as we share source code and cloning environments to assist you in your app development. And nontechnical readers can gain insight and details on how to develop an AI application.
Ideation & Planning
Kickoff your project by defining a common set of goals, data sources, technology limitations, the team, and a strategic plan.
Create Applications with Powerful AI Capabilities
Familiarize yourself with the tools, infrastructure, and techniques used in artificial intelligence development through the process of building a sample application.
Explore the creative process of turning a concept into a product. Identify your users, brainstorm and define use cases, and evaluate the feasibility of your idea.
The Anatomy of an AI Team
Understand the types of contributors you may need for your team, each role's required skills, and how to find the most appropriate person to fill that role.
Define the tasks required for your AI project by applying different project analysis and planning methodologies, and learn about general project management guidelines.
App Development & Deployment
Take your app from prototype to working application, and prepare it for production.
This final article provides step-by-step instructions on how to deploy web API services incorporating emotion recognition (image processing) and music generation, including a web app server with a user interface.