Machine learning is the most intelligent and cutting-edge research area in artificial intelligence. This paper utilizes the word2vec method to compare machine learning on Chinese academic and social Q&A platforms, aiming to promote research and practice in machine learning. Firstly, data were collected from Zhihu and the China National Knowledge Infrastructure (CNKI) platform to form corpora for the social Q&A platform and academic platform. Subsequently, two word2vec models were trained using these corpora. Next, a comparison between the social Q&A platform and the academic platform was conducted using the “20 most similar words to machine learning and deep learning.” Further, the word embeddings overview for both platforms was compared using t-SNE dimensionality reduction and matplotlib visualization methods. The research results reveal machine learning differences between Chinese academic and social Q&A platforms. This study innovatively employs the word2vec approach, combining Chinese academic and social Q&A platforms to provide a new perspective for machine learning research.