In fact, there are already many cases of applying deep learning technology in our real life.
For example, in the e-commerce industry, when browsing Taobao, there are many products on the page that match your hobbies and have recently been interested in purchasing. This kind of personalized recommendation involves deep learning technology, and The Taobao intelligent robot that can talk to you and solve your questions on the shopping interface also involves deep learning technology.
For example, in the transportation field, deep learning technology can detect vehicle parking, reverse driving and other behaviors, and even accurately identify the vehicle's license plate number, color, model, and people in the vehicle to assist traffic law enforcement, even in the event of a traffic accident. Call the police in case of traffic accidents and traffic jams, etc.
For example, in the financial industry, banks can use deep learning technology to analyze millions of consumer data (age, occupation, marital status, etc.), financial borrowing and insurance status (whether there are default records, repayment time, etc.) , vehicle accident records, etc.) are analyzed to determine whether loan services can be provided.
For example, in the home furnishing industry, smart home applications also use deep learning technology. For example, smart refrigerators use image recognition and other technologies to record the types of ingredients and users’ daily dietary data, and then analyze the user’s eating habits and analyze the user’s eating habits based on multi-dimensional Give the most comprehensive healthy meal advice.
For example, in the manufacturing industry, machine vision has been used in industrial automation systems for a long time, such as intelligent integrated testing of dashboards, automatic damage control on metal plate surfaces, automobile body inspection, banknote printing quality inspection, metallographic analysis, and assembly lines. In production inspection, etc., machine vision automation equipment can replace manual labor for tireless repetitive work, and in some dangerous working environments that are not suitable for manual work or situations where artificial vision cannot meet the requirements, machine vision can replace artificial vision.
There are also education industry, medical industry, etc. Deep learning technology has penetrated into various industries and fields.