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Titlebook: An Introduction to Machine Learning; Gopinath Rebala,Ajay Ravi,Sanjay Churiwala Book 2019 Springer Nature Switzerland AG 2019 Deep Learnin

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21#
發(fā)表于 2025-3-25 05:41:20 | 只看該作者
https://doi.org/10.1007/978-3-030-15729-6Deep Learning; Cloud computing; Big data; Feature Search/Convolution; Natural Language Processing
22#
發(fā)表于 2025-3-25 08:24:04 | 只看該作者
Springer Nature Switzerland AG 2019
23#
發(fā)表于 2025-3-25 12:52:40 | 只看該作者
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發(fā)表于 2025-3-25 15:54:47 | 只看該作者
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發(fā)表于 2025-3-25 23:35:44 | 只看該作者
https://doi.org/10.1007/978-3-662-59382-0categories are labelled, and models are generally learned from training data. Classification models can be created using simple thresholds, regression techniques, or other machine learning techniques like Neural Networks, Random Forests, or Markov models.
26#
發(fā)表于 2025-3-26 03:11:40 | 只看該作者
27#
發(fā)表于 2025-3-26 06:21:31 | 只看該作者
https://doi.org/10.1007/978-3-662-28879-5ariety of applications including speech recognition, language translations, summarization, question responses, speech generation, and search applications. NLP is an area of research which has proven to be difficult to master. Deep learning techniques have started to solve some of the issues involved in natural language processing.
28#
發(fā)表于 2025-3-26 09:08:32 | 只看該作者
29#
發(fā)表于 2025-3-26 14:34:26 | 只看該作者
30#
發(fā)表于 2025-3-26 17:24:32 | 只看該作者
Zur Geschichte der Umlaufgetriebe,nt learning models. Subsequent chapters will dive deeper into the various algorithms or applications that depend on these models. The primary learning models that will be considered are?Supervised, Unsupervised, Semi-supervised and Reinforcement learning.
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