Local Artificial Intelligence

This course is a comprehensive understanding of AI concepts and its application using Python and iPython

Artificial intelligence in animal production, Artificial intelligence in field crop production, Smart agriculture etc.

This book focuses on the emerging topic of embedded artificial intelligence and provides a systematic summary of its principles, platforms, and practices. In the section on principles, it analyzes three main approaches for implementing embedded artificial intelligence: cloud computing mode, local mode, and local-cloud collaborative mode. The book identifies five essential components for implementing embedded artificial intelligence: embedded AI accelerator chips, lightweight neural network algorithms, model compression techniques, compiler optimization techniques, and multi-level cascaded application frameworks. The platform section introduces mainstream embedded AI accelerator chips and software frameworks currently used in the industry. The practical part outlines the development process of embedded artificial intelligence and showcases real-world application examples with accompanying code.

Break new ground in problem-solving and decision-making by learning from AI

Starting AI automation agency, build AI chatbot, AI sales agent, lead generation automation, and find prospective client

Learn ML, NLP, Deep, Transfer and Reinforcement learning with IBM Watson, Tensorflow Sim, Keras, OpenAI Gym and more