BearX is my personal try to create self-sufficient Deep-Learning library which contains the best aspects (in my opinion) of both Keras and Pytorch frameworks, but most importantly I am working on this project to get in-depth knownledge about maths behind neural network and learn how to properly structure larger projects in Python.

from bearx.layers import Linear
from bearx.models import Sequential

model = Sequential()
model.add(Linear(2, 2), activation='relu')

# Before training we have to compile model
model.compile(loss='mse',
              optimizer='sgd')

• Sequential

• Linear (Dense)
• RNN
• (testing)
• (testing)

• Relu
• Tanh
• Sigmoid (testing)
• Softmax(testing)

• MSE
• Cross-Entropy (testing)

• SGD

• Zeros
• Ones
• Normal Distribution
• Uniform Distribution
• RNNinit

BearX supports only python 3.x

• Convolutional

• RMSprop
• Adam