目錄(83章)
倒序
- 封面
- 版權(quán)頁
- Credits
- About the Authors
- About the Reviewer
- www.PacktPub.com
- eBooks discount offers and more
- Preface
- What this book covers
- What you need for this book
- Who this book is for
- Conventions
- Reader feedback
- Customer support
- Chapter 1. First Steps to Scalability
- Explaining scalability in detail
- Python for large scale machine learning
- Python packages
- Summary
- Chapter 2. Scalable Learning in Scikit-learn
- Out-of-core learning
- Streaming data from sources
- Stochastic learning
- Feature management with data streams
- Summary
- Chapter 3. Fast SVM Implementations
- Datasets to experiment with on your own
- Support Vector Machines
- Feature selection by regularization
- Including non-linearity in SGD
- Hyperparameter tuning
- Summary
- Chapter 4. Neural Networks and Deep Learning
- The neural network architecture
- Neural networks and regularization
- Neural networks and hyperparameter optimization
- Neural networks and decision boundaries
- Deep learning at scale with H2O
- Deep learning and unsupervised pretraining
- Deep learning with theanets
- Autoencoders and unsupervised learning
- Summary
- Chapter 5. Deep Learning with TensorFlow
- TensorFlow installation
- Machine learning on TensorFlow with SkFlow
- Keras and TensorFlow installation
- Convolutional Neural Networks in TensorFlow through Keras
- CNN's with an incremental approach
- GPU Computing
- Summary
- Chapter 6. Classification and Regression Trees at Scale
- Bootstrap aggregation
- Random forest and extremely randomized forest
- Fast parameter optimization with randomized search
- CART and boosting
- XGBoost
- Out-of-core CART with H2O
- Summary
- Chapter 7. Unsupervised Learning at Scale
- Unsupervised methods
- Feature decomposition – PCA
- PCA with H2O
- Clustering – K-means
- K-means with H2O
- LDA
- Summary
- Chapter 8. Distributed Environments – Hadoop and Spark
- From a standalone machine to a bunch of nodes
- Setting up the VM
- The Hadoop ecosystem
- Spark
- Summary
- Chapter 9. Practical Machine Learning with Spark
- Setting up the VM for this chapter
- Sharing variables across cluster nodes
- Data preprocessing in Spark
- Machine learning with Spark
- Summary
- Appendix A. Introduction to GPUs and Theano
- GPU computing
- Theano – parallel computing on the GPU
- Installing Theano
- Index 更新時間：2021-07-14 10:40:06
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