Keras vs Numba: What are the differences?
## Key differences between Keras and Numba
Keras is a high-level neural networks API while Numba is a JIT compiler for Python code. One key difference lies in their primary focus: Keras is more tailored towards building and training deep learning models, whereas Numba is focused on optimizing Python code for better performance. In terms of usage, Keras is more commonly used in the field of machine learning for creating neural networks, while Numba is utilized for speeding up numerical computations.
Another significant difference is in their approach to optimization. Keras focuses on ease of use and abstracting complex computations, making it easier for developers to create neural network models quickly. On the other hand, Numba is more hands-on, allowing developers to specify which parts of the code to optimize and providing fine-grained control over the process.
Keras provides a higher level of abstraction, making it more user-friendly for developers who are new to deep learning, while Numba requires a deeper understanding of Python and optimization techniques to effectively use its capabilities. Additionally, Keras comes with a wide range of built-in functions and tools specifically designed for deep learning tasks, whereas Numba is more versatile and can be used for optimizing various types of Python code beyond just neural networks.
One notable difference is in their compatibility with hardware acceleration. Keras has better support for running on GPUs and TPUs, allowing for faster training of deep learning models on specialized hardware. On the contrary, Numba's optimizations are more focused on improving the performance of code on the CPU, making it a preferred choice for tasks that do not heavily rely on GPU acceleration.
In conclusion, Keras is ideal for developers looking to quickly build and train deep learning models with minimal optimization effort, while Numba is better suited for those who require fine-tuning and customization for specific performance improvements in numerical computations.
In Summary, Keras is primarily focused on building neural networks for deep learning with a high level of abstraction, while Numba is a JIT compiler aimed at optimizing Python code for improved performance.
