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10 Popular Machine Learning Frameworks
- Optimized for performance
- Developer friendly. The framework utilizes traditional ways of building models.
- Is easy to understand and code on
- Is not completely a black box
- Provide parallelization to distribute the computation process
- Mathematically Expressive Scala DSL
- Support for Multiple Distributed Backends (including Apache Spark)
- Modular Native Solvers for CPU/GPU/CUDA Acceleration