{"id":36639,"date":"2024-11-01T09:50:12","date_gmt":"2024-11-01T09:50:12","guid":{"rendered":"http:\/\/atmokpo.com\/w\/?p=36639"},"modified":"2024-11-01T11:52:24","modified_gmt":"2024-11-01T11:52:24","slug":"deep-learning-pytorch-course-start-with-kaggle","status":"publish","type":"post","link":"https:\/\/atmokpo.com\/w\/36639\/","title":{"rendered":"Deep Learning PyTorch Course, Start with Kaggle"},"content":{"rendered":"

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With the advancement of deep learning, AI technology is rapidly evolving in various fields. In particular, its application in the field of data science is prominent, and many people are studying through various online platforms to learn machine learning and deep learning. Among them, Kaggle<\/strong> is an all-in-one platform for data scientists and machine learning engineers that provides a variety of datasets and problems. In this article, we will explore how to gain practical experience on Kaggle using PyTorch.<\/p>\n

1. What is PyTorch?<\/h2>\n

PyTorch is an open-source machine learning framework developed by Facebook AI Research (FAIR), and it is very useful for building and training deep learning models. In particular, it supports dynamic computation graphs, which provide flexibility and readability in code, making it easy to implement complex models.<\/p>\n

1.1. Key Features of PyTorch<\/h3>\n