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Features

1. Responsive Construct 2. Flexible 3. Easily Trainable 4. Parallel Neural Network Training 5. Large Community 6. Open Source

1

1. Cross-validation 2. Unsupervised learning algorithms 3. Feature extraction:

Features

2

1. Interactive 2. Mathematics 3. Intuitive 4. Lot of Interaction

3

Features

1. Runs smoothly on both CPU and GPU 2. Supports almost all the models of a neural network 3. Incredibly expressive, flexible, and apt for innovative research 4. Easy to debug and explore

4

Features

1. Hybrid Front-End 2. Distributed Training 3. Python First 4. Libraries And Tools

5

Features

1. Very fast computation 2. Intuitive 3. Faster training 4. Will not produce errors

6

Features

Eli5 supports wother libraries XGBoost, lightning, scikit-learn, and sklearn-crfsuite libraries.

7

Features

1. Developed using NumPy 2. Provides all the efficient numerical routines

8

Features

1. Tight integration with NumPy 2. Transparent use of a GPU 3. Efficient symbolic differentiation 4. Speed and stability optimizations 5. Dynamic C code generation

9

Features

1. Easy Data Manipulation 2. Support for operations

10

Features

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