توضیحات
Machine Learning with PyTorch and Scikit-Learn provides a hands-on guide to building machine learning and deep learning models using Python. Readers learn to implement supervised and unsupervised learning algorithms, neural networks, and deep learning pipelines. The book covers data preprocessing, model evaluation, optimization, and deployment, with practical examples in computer vision, natural language processing, and predictive analytics. By combining Scikit-Learn for classical ML models and PyTorch for deep learning, Sebastian Raschka equips readers with the skills to develop robust, efficient, and scalable AI applications. Suitable for students, data scientists, and developers, the book emphasizes practical implementation while explaining underlying mathematical concepts.
نقد و بررسیها
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