为机器学习的入门者提供多种基于实例的sklearn、TensorFlow以及自编函数(AnFany)的ML算法程序。

Machine learning: Practical applications

🏠 A shop-rental-and-selling platform that ranks the shops for users

The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. [2020]

An exhilarating journey of 100 Days, 100 Programs challenge, where I explore various programming languages and frameworks to build a diverse collection of practical applications.

A practical application for drawing aftermaths. Application written in Python 3.12.2 with the random library

An application to help select a programming course for children. The application is written 100% in the programming language Python3.12.2. The application uses the Random library. The design took into account the readability and cleanliness of the code

📚 A practical approach to machine learning.

Práctica 2: Fundamentos de la Programación

Deals with the applications of basic mathematical models in business decision making. It includes model formulation, linear programming, network analysis, decision theory, inventory problems, queuing, regression and demand forecasting, and simulation models.