Difference between revisions of "Optimizer"
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There are many options for optimizer in Tensorflow. Optimizers are the tool to minimise [[loss]] between prediction and real value. [http://keras.io/optimizers/ Click here For a list of Keras optimizer functions.] | There are many options for optimizer in Tensorflow. Optimizers are the tool to minimise [[loss]] between prediction and real value. [http://keras.io/optimizers/ Click here For a list of Keras optimizer functions.] | ||
| + | ---- | ||
| + | ::<code> model.compile(optimizer='[[Average-Stochastic Gradient Descent (SGD) Weight-Dropped LSTM (AWD-LSTM) |sgd]]'. [[loss]]='mean_squared_error')</code> | ||
| + | ---- | ||
<youtube>cJA5IHIIL30</youtube> | <youtube>cJA5IHIIL30</youtube> | ||
Revision as of 09:04, 31 August 2019
YouTube search... ...Google search
- Loss Functions
- TensorFlow Training Classes Python API
- Gradient Descent Optimization & Challenges
- Objective vs. Cost vs. Loss vs. Error Function
- H2O Driverless AI - Intro + Interactive Hands-on Lab - Video
There are many options for optimizer in Tensorflow. Optimizers are the tool to minimise loss between prediction and real value. Click here For a list of Keras optimizer functions.
Genetic Algorithm Optimization
