TensorFlow: 100 Tips and Strategies For Building, Training, and Deploying Models

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Here are 100 tips for working with TensorFlow, a widely-used open-source machine learning framework:

Basics of TensorFlow:

1. Import TensorFlow with import tensorflow as tf.
2. Install TensorFlow using pip install tensorflow.
3. Access TensorFlow version with tf.__version__.
4. Create a constant tensor with tf.constant().
5. Use tf.Variable() for mutable tensors.

Tensor Operations:

1. Perform basic arithmetic operations on tensors.
2. Use tf.matmul() for matrix multiplication.
3. Reshape tensors with tf.reshape().
4. Concatenate tensors along specified axes with tf.concat().
5. Use tf.reduce_mean() for computing mean along dimensions.

Variables and Gradients:

1. Enable automatic differentiation with tf.GradientTape.
2. Access gradients with respect to variables using tape.gradient.
3. Implement custom gradients with tf.custom_gradient.
4. Use tf.Variable to define trainable variables.