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Revision as of 07:04, 6 May 2018
Contents
Overview
Models
- Deep Learning Roadmap
- Deep Neural Networks
- Convolutional Neural Networks
- Generative Adversarial Networks (GANs)
- Sequence to Sequence (Seq2Seq)
Techniques & Coding
- Data Preprocessing & Feature Exploration
- Activation Functions
- Optimizers
- Pooling
- Hyperparameters
- Visualization
- Transfer Learning
- Competitions
- Repositories
- Python
Frameworks
TensorFlow
Other DL Frameworks
Platforms: Machine Learning as a Service (MLaaS)
Amazon AWS
Microsoft Azure
Google Cloud AI
Research & Development
- Self Learning
- Explainable Artificial Intelligence
- Capsule Networks (CapNets)
- Messaging & Routing
- Deep Distributed Q Network Partial Observability
- Deep Reinforcement Learning
- Genetic Algorithms
- Natural Language Inference (NLI) and Recognizing Textual Entailment (RTE)
- 3D Simulation Environments
- Other Challenges
