1. Advanced Machine Learning with R : Tackle data analytics and machine learning challenges and build complex applications with R 3.5 /: Tackle data analytics and machine learning challenges and build complex applications with R 3.5. (2019) Authors: Lesmeister, Cory; Dr, Chinnamgari, Sunil Kumar Record Type: Book Extent: 1 online resource (664 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
2. Applied Deep Learning with Keras : Solve complex real-life problems with the simplicity of Keras /: Solve complex real-life problems with the simplicity of Keras. (2019) Authors: Bhagwat, Ritesh; Abdolahnejad, Mahla; Moocarme, Matthew Record Type: Book Extent: 1 online resource (412 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
3. Applied Supervised Learning with R : Use machine learning libraries of R to build models that solve business problems and predict future trends /: Use machine learning libraries of R to build models that solve business problems and predict future trends. (2019) Authors: Ramasubramanian, Karthik; Moolayil, Jojo Record Type: Book Extent: 1 online resource (502 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
4. Applied Unsupervised Learning with R : Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA /: Uncover hidden relationships and patterns with k-means clustering, hierarchical clustering, and PCA. (2019) Authors: Malik, Alok; Tuckfield, Bradford Record Type: Book Extent: 1 online resource (320 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
5. Caffe2 Quick Start Guide : Modular and scalable deep learning made easy /: Modular and scalable deep learning made easy. (2019) Authors: Nanjappa, Ashwin Record Type: Book Extent: 1 online resource (136 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
6. Ensemble Machine Learning Cookbook : Over 35 practical recipes to explore ensemble machine learning techniques using Python /: Over 35 practical recipes to explore ensemble machine learning techniques using Python. (2019) Authors: Sarkar, Dipayan; Natarajan, Vijayalakshmi Record Type: Book Extent: 1 online resource (336 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
7. Hands-On Deep Learning Architectures with Python : Create deep neural networks to solve computational problems using TensorFlow and Keras /: Create deep neural networks to solve computational problems using TensorFlow and Keras. (2019) Authors: Liu, Yuxi (Hayden); Mehta, Saransh Record Type: Book Extent: 1 online resource (316 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
8. Hands-On Deep Learning for IoT : Train neural network models to develop intelligent IoT applications /: Train neural network models to develop intelligent IoT applications. (2019) Authors: Karim, Md. Rezaul Record Type: Book Extent: 1 online resource (308 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
9. Hands-On Generative Adversarial Networks with PyTorch 1.x : Implement next-generation neural networks to build powerful GAN models using Python /: Implement next-generation neural networks to build powerful GAN models using Python. (2019) Authors: Hany, John; Walters, Greg Record Type: Book Extent: 1 online resource (312 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗
10. Hands-On Neural Networks : Learn how to build and train your first neural network model using Python /: Learn how to build and train your first neural network model using Python. (2019) Authors: De Marchi, Leonardo; Mitchell, Laura Record Type: Book Extent: 1 online resource (280 pages) View Content: Available online (eLD content is only available in our Reading Rooms) ↗