Machine Learning for Engineers

Machine Learning for Engineers

Using data to solve problems for physical systems

McClarren, Ryan G.

Springer Nature Switzerland AG

09/2022

247

Mole

Inglês

9783030703905

15 a 20 dias

407

Descrição não disponível.
Part I Fundamentals.- 1. Introduction.- 2. The landscape of machine learning.- 3. Linear models.- 4. Tree-based models.- 5. Clustering data.- Part II Deep Neural Networks.- 6. Feed-forward Neural networks.- 7.convolutional neural networks.- 8. Recurrent neural networks for time series data.- Part III Advanced topics in machine learning.- 9. Unsupervised learning with neural networks.- 10. Reinforcement learning.- 11. Transfer learning.- Part IV Appendixes.- Appendix A. Sci-Kit learn.- Appendix B. Tensorflow.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
supervised learning;unsupervised learning;Bayesian statistics;linear models;tree-based models;deep neural networks;convolutional neural networks;SciKit-Learn;Tensorflow;backpropogation