Difference between revisions of "Optimizer"
| Line 8: | Line 8: | ||
[http://www.google.com/search?q=optimizers+machine+learning+ML+artificial+intelligence ...Google search] | [http://www.google.com/search?q=optimizers+machine+learning+ML+artificial+intelligence ...Google search] | ||
| − | * [[Loss]] | + | * [[Loss]] Functions |
* [https://www.tensorflow.org/api_guides/python/train TensorFlow Training Classes Python API] | * [https://www.tensorflow.org/api_guides/python/train TensorFlow Training Classes Python API] | ||
* [[Gradient Descent Optimization & Challenges]] | * [[Gradient Descent Optimization & Challenges]] | ||
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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 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.] |
| + | |||
<youtube>cJA5IHIIL30</youtube> | <youtube>cJA5IHIIL30</youtube> | ||
Revision as of 08:42, 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
