Summary of previous AI courses

Friends who often follow <Everyone is a Geek> should know that I have written two series of courses on artificial intelligence before. Due to the fragmentation of the time of article release and the unsystematic distribution, it is easy to cause confusion to readers. Here is a summary of these two series of courses. The course is divided into two parts: "Object Recognition" and "Model Training". Through the use of tensorflow on Android, you can thoroughly understand the practical application of artificial intelligence, so that you can recognize the objects you want to recognize through the model you trained. Personally, I think artificial intelligence is divided into three stages, namely the algorithm dividend period, the engineering dividend period, and the platform dividend period. Obviously, artificial intelligence is still in the stage of algorithm research, but these two series of courses will not explain the principle essence from the perspective of algorithm. It is mainly from the perspective of application to teach you the application development of artificial intelligence, so that artificial intelligence beginners can easily enter the door of artificial intelligence.

The two series of courses are listed below:

Object Recognition:

• Lesson 1: Opportunities for AI in Embedded Systems

• Lesson 2: Preparation before developing a machine learning app

• Lesson 3: Importing tensorflow, models and test data into Android projects
  

• Lesson 4: Using the Model

• Lesson 5: Visualization of Inference Results

Model training:

• 1. Preparation for training model

• 2. Training model to run a demo

• 3. Training model: Installation of environment for training on GPU

• 4. Training model: preparing training data

• 5. Training model: using the trained model to identify objects

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