A comprehensive guide to deep learning for web development, specifically with Python. It covers the foundational concepts of machine learning and neural networks, including various types like CNNs and RNNs, and essential terminology such as bias, variance, overfitting, and underfitting. The sources provide practical instruction on building and deploying deep learning web applications using frameworks like Flask and Django, integrating with cloud platforms such as AWS, Google Cloud Platform, and Microsoft Azure, and utilizing services like TensorFlow.js and Dialogflow. Furthermore, the text addresses crucial aspects of security, monitoring, and performance optimization in production environments, explores the evolution and impact of AI on the web, and discusses natural language processing (NLP) for applications like chatbots.
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Published on 2 days, 6 hours ago
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