ailearning

A Chinese language learning resource hosted by ApacheCN that follows the Machine Learning in Action book and adds linear algebra, PyTorch, NLTK, and TensorFlow 2.

The GitHub description lists the territory: data analysis, machine learning in action, linear algebra, PyTorch, NLTK, and TensorFlow 2. The README documents a machine learning basics section with Python version support notes, and a table of learning documents organized by chapter and maintainer. The content is written in Chinese and aimed at Chinese speaking learners, and the project is hosted by the ApacheCN organization with a homepage at ailearning.apachecn.org.

The learning document table follows the Machine Learning in Action book, listing chapters on machine learning basics, KNN nearest neighbor, decision trees, naive Bayes, Logistic regression, and SVM support vector machines. Later chapters cover ensemble methods, regression, tree regression, K means clustering, and Apriori association analysis. Each chapter lists a responsible maintainer and a contact QQ number, which gives the project a community maintained feel.

The README discusses video resources and is surprisingly honest about them. It mentions that some learners find Andrew Ng videos hard to follow, and describes a recommendation to try Machine Learning in Action as an accessible introduction. Video sites listed include Youku, bilibili, Acfun, and NetEase Cloud Classroom, with a recommendation for a professor's machine learning notes. That kind of practical study advice is common in Chinese learning communities and rare in most English resources.

The README lists data sources including a unified data address, a Baidu cloud package address, book download addresses, and specific addresses for machine learning, deep learning, and recommendation system data. The project rounds out with a homepage at ailearning.apachecn.org. For learners who need not just explanations but the actual datasets to work through, having those addresses collected in one place saves a lot of hunting.

AiLearning works best as a companion to a book many find dense, with chapter notes, maintainers to contact, and datasets collected in one place. The candid notes about which videos are hard to follow give it a realistic tone.

• Source 1 · Project repository
• Source 2 · README