Difference between revisions of "Optimizer"
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* [http://videos.h2o.ai/watch/4Qx2eUbrsUCZ4rThjtVxeb H2O Driverless AI - Intro + Interactive Hands-on Lab - Video] | * [http://videos.h2o.ai/watch/4Qx2eUbrsUCZ4rThjtVxeb 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. There are many different weights a model could learn, and brute-force testing every one would take forever. Instead, an optimizer is chosen which evaluates the [[loss]] value, and smartly updates the weights. [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. There are many different weights a model could learn, and brute-force testing every one would take forever. Instead, an optimizer is chosen which evaluates the [[loss]] value, and smartly updates the weights. [http://keras.io/optimizers/ Click here For a list of Keras optimizer functions.] Optimizer is one of the two parameters required to compile a model... |
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Revision as of 09:24, 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. There are many different weights a model could learn, and brute-force testing every one would take forever. Instead, an optimizer is chosen which evaluates the loss value, and smartly updates the weights. Click here For a list of Keras optimizer functions. Optimizer is one of the two parameters required to compile a model...
Genetic Algorithm Optimization
