A basic knowledge of Python and a limited understanding of machine learning will be beneficial.
- Title Page
- Copyright and Credits
- About Packt
- Contributors
- Preface
- Section 1: Introduction and Foundation
- Introduction to IBM Cloud
- Feature Extraction - A Bag of Tricks
- Supervised Machine Learning Models for Your Data
- Implementing Unsupervised Algorithms
- Section 2: Tools and Ingredients for Machine Learning in IBM Cloud
- Machine Learning Workouts on IBM Cloud
- Using Spark with IBM Watson Studio
- Deep Learning Using TensorFlow on the IBM Cloud
- Section 3: Real-Life Complete Case Studies
- Creating a Facial Expression Platform on IBM Cloud
- The Automated Classification of Lithofacies Formation Using ML
- Building a Cloud-Based Multibiometric Identity Authentication Platform
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