Hands-on unsupervised learning using Python: how to build applied machine learning solutions from unlabeled data/
Patel, Ankur A.
Hands-on unsupervised learning using Python: how to build applied machine learning solutions from unlabeled data/ Ankur A. Patel - Kolkata: Shroff Publishers, 2019. - xix, 337 p. : ill. ; 24 cm.
Part 1. Fundamentals of unsupervised learning. Unsupervised learning in the machine learning ecosystem --
End-to-end machine learning project --
Part 2. Unsupervised learning using Scikit-learn. Dimensionality reduction --
Anomaly detection --
Clustering --
Group segmentation --
Part 3. Unsupervised learning using TensorFlow and Keras. Autoencoders --
Hands-on autoencoder --
Semisupervised learning --
Part 4. Deep unsupervised learning using TensorFlow and Keras. Recommender systems using restricted Boltzmann machines --
Feature detection using deep belief networks --
Generative adversarial networks --
Time series clustering --
Conclusion.
9781492035640 9789352138128
Python (Computer program language)
Machine learning
Artificial intelligence
005.133 / PAT/H
Hands-on unsupervised learning using Python: how to build applied machine learning solutions from unlabeled data/ Ankur A. Patel - Kolkata: Shroff Publishers, 2019. - xix, 337 p. : ill. ; 24 cm.
Part 1. Fundamentals of unsupervised learning. Unsupervised learning in the machine learning ecosystem --
End-to-end machine learning project --
Part 2. Unsupervised learning using Scikit-learn. Dimensionality reduction --
Anomaly detection --
Clustering --
Group segmentation --
Part 3. Unsupervised learning using TensorFlow and Keras. Autoencoders --
Hands-on autoencoder --
Semisupervised learning --
Part 4. Deep unsupervised learning using TensorFlow and Keras. Recommender systems using restricted Boltzmann machines --
Feature detection using deep belief networks --
Generative adversarial networks --
Time series clustering --
Conclusion.
9781492035640 9789352138128
Python (Computer program language)
Machine learning
Artificial intelligence
005.133 / PAT/H