Optimizer - Revision history

BPeat at 01:30, 6 March 2024

2024-03-06T01:30:47Z

2024-03-06T01:29:49Z

2024-03-06T01:29:23Z

2024-03-06T01:22:37Z

2023-11-29T02:44:34Z

2023-08-06T13:49:25Z

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@@ Line 17: / Line 17: @@
 [http://www.google.com/search?q=optimizers+machine+learning+ML+artificial+intelligence ...Google search]
 * [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Train, Validate, and Test]]
 * [[Backpropagation]] ... [[Feed Forward Neural Network (FF or FFNN)|FFNN]] ... [[Forward-Forward]] ... [[Activation Functions]] ...[[Softmax]] ... [[Loss]] ... [[Boosting]] ... [[Gradient Descent Optimization & Challenges|Gradient Descent]] ... [[Algorithm Administration#Hyperparameter|Hyperparameter]] ... [[Manifold Hypothesis]] ... [[Principal Component Analysis (PCA)|PCA]]
 * [http://www.tensorflow.org/api_guides/python/train TensorFlow Training Classes Python API]

@@ Line 20: / Line 20: @@
 * [[Agents#AI Agent Optimization|AI Agent Optimization]] ... [[Optimization Methods]] ... [[Optimizer]] ... [[Objective vs. Cost vs. Loss vs. Error Function]] ... [[Exploration]]
 * [[Backpropagation]] ... [[Feed Forward Neural Network (FF or FFNN)|FFNN]] ... [[Forward-Forward]] ... [[Activation Functions]] ...[[Softmax]] ... [[Loss]] ... [[Boosting]] ... [[Gradient Descent Optimization & Challenges|Gradient Descent]] ... [[Algorithm Administration#Hyperparameter|Hyperparameter]] ... [[Manifold Hypothesis]] ... [[Principal Component Analysis (PCA)|PCA]]
 * [http://www.tensorflow.org/api_guides/python/train TensorFlow Training Classes Python API]
 * [http://videos.h2o.ai/watch/4Qx2eUbrsUCZ4rThjtVxeb H2O Driverless AI - Intro + Interactive Hands-on Lab - Video]

@@ Line 17: / Line 17: @@
 [http://www.google.com/search?q=optimizers+machine+learning+ML+artificial+intelligence ...Google search]
-* [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Optimizer]] ... [[Train, Validate, and Test]]
+* [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Train, Validate, and Test]]
-* [[Optimization Methods]]
+* [[Agents#AI Agent Optimization|AI Agent Optimization]] ... [[Optimization Methods]] ... [[Optimizer]] ... [[Objective vs. Cost vs. Loss vs. Error Function]] ... [[Exploration]]
 * [[Backpropagation]] ... [[Feed Forward Neural Network (FF or FFNN)|FFNN]] ... [[Forward-Forward]] ... [[Activation Functions]] ...[[Softmax]] ... [[Loss]] ... [[Boosting]] ... [[Gradient Descent Optimization & Challenges|Gradient Descent]] ... [[Algorithm Administration#Hyperparameter|Hyperparameter]] ... [[Manifold Hypothesis]] ... [[Principal Component Analysis (PCA)|PCA]]
 * [[Objective vs. Cost vs. Loss vs. Error Function]]

@@ Line 18: / Line 18: @@
 * [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Optimizer]] ... [[Train, Validate, and Test]]
 * [[Backpropagation]] ... [[Feed Forward Neural Network (FF or FFNN)|FFNN]] ... [[Forward-Forward]] ... [[Activation Functions]] ...[[Softmax]] ... [[Loss]] ... [[Boosting]] ... [[Gradient Descent Optimization & Challenges|Gradient Descent]] ... [[Algorithm Administration#Hyperparameter|Hyperparameter]] ... [[Manifold Hypothesis]] ... [[Principal Component Analysis (PCA)|PCA]]
 * [[Objective vs. Cost vs. Loss vs. Error Function]]

@@ Line 22: / Line 22: @@
 * [http://www.tensorflow.org/api_guides/python/train TensorFlow Training Classes Python API]
 * [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 [[Activation Functions#Weights|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 [[Activation Functions#Weights|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...

← Older revision		Revision as of 13:49, 6 August 2023
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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.] Optimizer is one of the two parameters required to compile a model...	+	There are many options for optimizer in [[TensorFlow]]. Optimizers are the tool to minimise [[loss]] between prediction and real value. There are many different [[Activation Functions#Weights\|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 [[Activation Functions#Weights\|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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 * [[AI Solver]] ... [[Algorithms]] ... [[Algorithm Administration|Administration]] ... [[Model Search]] ... [[Discriminative vs. Generative]] ... [[Optimizer]] ... [[Train, Validate, and Test]]
 * [[Loss]] Functions
 * [[Gradient Descent Optimization & Challenges]]
 * [[Objective vs. Cost vs. Loss vs. Error Function]]

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 |title=PRIMO.ai
 |titlemode=append
-|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
+|keywords=ChatGPT, artificial, intelligence, machine, learning, GPT-4, GPT-5, NLP, NLG, NLC, NLU, models, data, singularity, moonshot, Sentience, AGI, Emergence, Moonshot, Explainable, TensorFlow, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Hugging Face, OpenAI, Tensorflow, OpenAI, Google, Nvidia, Microsoft, Azure, Amazon, AWS, Meta, LLM, metaverse, assistants, agents, digital twin, IoT, Transhumanism, Immersive Reality, Generative AI, Conversational AI, Perplexity, Bing, You, Bard, Ernie, prompt Engineering LangChain, Video/Image, Vision, End-to-End Speech, Synthesize Speech, Speech Recognition, Stanford, MIT |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 |description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
 }}
 [http://www.youtube.com/results?search_query=optimizers+deep+learning YouTube search...]
 [http://www.google.com/search?q=optimizers+machine+learning+ML+artificial+intelligence ...Google search]
 * [[Loss]] Functions
 * [[Gradient Descent Optimization & Challenges]]
 * [[Objective vs. Cost vs. Loss vs. Error Function]]