What are some recommended learning paths for someone interested in specializing in deep learning after having a foundation in machine learning?

The distinction between narrow and general intelligence is already apparent in the ... of machine learning, most commonly used to refer to deep neural networks. Feb 12, 2025 ... ... machine learning by efficiently targeting the most informative samples for model training ... deep learning works well with large amounts of ... Jun 26, 2023 ... Difference Between Active Learning and Passive Learning ... of machine learning models by selecting the most informative samples for labeling. May 21, 2024 ... Recently, information systems researchers also called for empowering machine learning ... learn the pattern of targeting different prospects. Mar 7, 2024 ... New technologies such as machine learning, natural language ... MDM can be identified as three main forms of informational activity that can cause ... Mar 24, 2024 ... Graph neural networks (GNNs) have achieved state-of-the-art results on many graph representation learning tasks by exploiting statistical ... May 17, 2019 ... ... Machine Learning Blog, a spinoff of the Machine Learning Department at Carnegie Mellon University. Feb 7, 2024 ... A multi-layer perceptron (MLP) is a type of artificial neural network consisting of multiple layers of neurons. Sep 5, 2018 ... A second advantage of convets is that they ob- tain better results in terms of accuracy than shallow machine learning systems. [8,13] . It is ... ... different deep neural networks to demonstrate that our method is independent of both architecture and data domain. We call our method DMI and compare it ...