KotlinDeepLearningTutorial
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20 hours ago •
zaleslaw
zaleslaw
Tensors, Model Inference, Linear Regression, MNIST, LSTM with TensorFlow, DL4j, komputation, DJL on Kotlin
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val conv1Weights: Variable = tf.variable(Shape.make(5L, 5L, NUM_CHANNELS, 32), Float::class.javaObjectType) val conv1Biases: Variable = tf.variable(Shape.make(32), Float::class.javaObjectType) Could be rewritten in the tf.variable(Shape.make(32)) via extension functions inline with reified types
1. Tensor calculations 2. Inference (with MNIST) 3. Graph for forward pass (optional) 4. LinReg (optional) 5. MNIST (2-3 layers) 6. LSTM (optional)