1, Python in machine learning
Python environment construction and its basic grammar learning; Familiar with basic concepts such as list tuples and the form of python functions; IO operation of Python; Introduction to the use of classes in Python; Python explains the classic algorithms, models and tasks in the field of machine learning with examples.
2. Mathematical basis of artificial intelligence
Familiar with symbolic representation in mathematics; Understand the law of function derivative and chain derivative; Understand the concept of function in mathematics; Familiar with matrix related concepts and mathematical expressions.
3. The concept and introduction of machine learning
Understand the related concepts involved in artificial intelligence; Understand how to obtain data and feature engineering; Familiar with data preprocessing methods; Understand the model training process; Familiar with the use of pandas; Remove the complexity of visualization process; Instructions for panda use; Graphic drawing.
4. Mathematical basis of machine learning-mathematical analysis
Master and understand the underlying mathematical theory support of artificial intelligence technology; Introduce probability theory, matrix and convex optimization, corresponding algorithm design and principle; Convex optimization theory, flow optimization means SGD, Newton method and other optimization methods.
5. TensorFlow, a deep learning framework.
Understand and learn variable scope and variable naming; Construct a multi-layer neural network and complete the optimization.
The task of artificial intelligence trainer
1, marking and processing the original data of services such as pictures, words and sounds;
2. Analyze and refine the characteristics of professional fields, and train and evaluate the related algorithms, functions and performances of artificial intelligence products;
3. Design the interactive process and application solution of artificial intelligence products;
4. Monitor, analyze and manage the application data of artificial intelligence products;
5. Adjust and optimize the parameters and configuration of artificial intelligence products.