Deep learning has rapidly evolved from a niche field into a transformative technology across industries, and making it accessible to a broader audience is a key challenge. Jeremy Howard and Sylvain Gugger address this challenge by demystifying deep learning through practical, code-first approaches in their guide, aimed especially at programmers eager to apply advanced AI techniques without requiring a mathematics PhD. By leveraging the fastai library and PyTorch framework, the authors empower readers to build state-of-the-art models from the outset while understanding the underlying principles that drive them.

• Deep learning can be...
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