TensorFlow: Core Concepts & Tensors TensorFlow is Google's open-source machine learning framework. TF 2.x uses eager execution by default (compute immediately) and Keras as its primary high-level API. Used for neural net…
ReadTensorFlow: Building Models with Keras Sequential API import tensorflow as tf from tensorflow import keras # Sequential — for simple linear stacks of layers model = keras.Sequential([ keras.layers.Input(shape=(784,)), ke…
ReadTensorFlow: Training Optimization Optimizers Adam: adaptive learning rate per parameter — best default choice for most problems SGD + momentum: often better final accuracy than Adam with proper lr schedule RMSprop: good …
ReadTensorFlow: Deployment Saving & Loading Models # Save in Keras format (recommended for TF/Keras) model.save('model.keras') model = keras.models.load_model('model.keras') # SavedModel format (for TF Serving, TFLite conver…
ReadSave this stack to your personal DevRecall — add your own notes, track what you're learning, and share what you know with the community.
Get started — free forever