Difference between revisions of "TensorFlow"

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|title=PRIMO.ai
 
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|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS  
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|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
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|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools  
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[http://www.youtube.com/results?search_query=TensorFlow+deep+learning+artificial+intelligence Youtube search...]
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[https://www.youtube.com/results?search_query=TensorFlow YouTube]
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[http://www.google.com/search?q=TensorFlow+deep+learning+artificial+intelligence+ML ...Google search]
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[https://www.quora.com/search?q=TensorFlow ... Quora]
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[https://www.google.com/search?q=TensorFlow ...Google search]
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[https://news.google.com/search?q=TensorFlow ...Google News]
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[https://www.bing.com/news/search?q=TensorFlow&qft=interval%3d%228%22 ...Bing News]
  
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* [[Python]] ... [[Generative AI with Python|GenAI w/ Python]] ... [[JavaScript]] ... [[Generative AI with JavaScript|GenAI w/ JavaScript]] ... [[TensorFlow]] ... [[PyTorch]]
 
* [[Google]] offerings
 
* [[Google]] offerings
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* [[Libraries & Frameworks]]
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* [[Libraries & Frameworks Overview]] ... [[Libraries & Frameworks]] ... [[Git - GitHub and GitLab]] ... [[Other Coding options]]
 
* TensorFlow is a [[Python]] library
 
* TensorFlow is a [[Python]] library
 
* [[Keras]] (currently part of TensorFlow 2.0)
 
* [[Keras]] (currently part of TensorFlow 2.0)
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* [[Analytics]] ... [[Visualization]] ... [[Graphical Tools for Modeling AI Components|Graphical Tools]] ... [[Diagrams for Business Analysis|Diagrams]] & [[Generative AI for Business Analysis|Business Analysis]] ... [[Requirements Management|Requirements]] ... [[Loop]] ... [[Bayes]] ... [[Network Pattern]]
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* [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless]] ... [[Hugging Face]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
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* [[Gaming]] ... [[Game-Based Learning (GBL)]] ... [[Games - Security|Security]] ... [[Game Development with Generative AI|Generative AI]] ... [[Metaverse#Games - Metaverse|Games - Metaverse]] ... [[Games - Quantum Theme|Quantum]] ... [[Game Theory]] ... [[Game Design | Design]]
 
* [http://venturebeat.com/2019/09/30/google-launches-tensorflow-2-0-with-tighter-keras-integration/ Google launches TensorFlow 2.0 with tighter Keras integration | Khari Johnson]
 
* [http://venturebeat.com/2019/09/30/google-launches-tensorflow-2-0-with-tighter-keras-integration/ Google launches TensorFlow 2.0 with tighter Keras integration | Khari Johnson]
 
* [[TensorFlow.js]]  ... Browser and Node Server
 
* [[TensorFlow.js]]  ... Browser and Node Server
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* [[TensorFlow Serving]]  .. Cloud, On-prem ...support model versioning (for model updates with a rollback option) and multiple models (for experimentation via A/B testing)
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* [[TensorFlow Serving]]  .. Cloud, On-prem ...support model versioning (for model updates with a rollback option) and multiple models (for experimentation via [[AI Verification and Validation#A/B Testing|A/B testing]])
 
* [[TensorFlow Lite]] ... Android, iOS, Raspberry Pi
 
* [[TensorFlow Lite]] ... Android, iOS, Raspberry Pi
 
** [[Converting to TensorFlow Lite]] convert models into TensorFlow Lite format  
 
** [[Converting to TensorFlow Lite]] convert models into TensorFlow Lite format  
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* TensorFlow [[Federated]]
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* TensorFlow [[Decentralized: Federated & Distributed|Federated]]
 
* [[TensorFlow Extended (TFX)]] an end-to-end platform for deploying production ML pipelines
 
* [[TensorFlow Extended (TFX)]] an end-to-end platform for deploying production ML pipelines
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* [http://playground.tensorflow.org TensorFlow Playground]
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* [[TensorFlow Playground]]
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* [[TensorBoard]] with embedding projector - visualization of high-dimensional data
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* [[TensorBoard]] with [http://projector.tensorflow.org/ Embedding Projector] - visualization of high-dimensional data
 
* [http://ai.google/tools/ We’re making tools and resources available so that anyone can use technology to solve problems | Google AI]
 
* [http://ai.google/tools/ We’re making tools and resources available so that anyone can use technology to solve problems | Google AI]
 
* [http://github.com/tensorflow/workshops TensorFlow Workshops] click on links to run in [[Colaboratory]] (Colab)
 
* [http://github.com/tensorflow/workshops TensorFlow Workshops] click on links to run in [[Colaboratory]] (Colab)
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** [[TFLearn]]
 
** [[TFLearn]]
 
** [[Swift]]  
 
** [[Swift]]  
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* [https://www.altexsoft.com/blog/datascience/the-best-machine-learning-tools-experts-top-picks/ Best Machine Learning Tools: Experts’ Top Picks | Altexsoft]
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* [https://blog.tensorflow.org/2023/07/whats-new-in-tensorflow-213-and-keras-213.html What's new in TensorFlow 2.13 and Keras 2.13? | TensorFlow & Keras Teams]
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http://jaxenter.com/wp-content/uploads/2019/01/tensorflow-2-1-768x426.png
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<img src="https://content.altexsoft.com/media/2017/08/tensors_flowing-1.gif" width="400">
  
  
 
* [[Coding TensorFlow]] <--- video series
 
* [[Coding TensorFlow]] <--- video series
  
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= TensorFlow 2.0 =
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TensorFlow focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs, and flexible model building on any platform, tight [[Keras]] integration. You can easily ingest datasets via tf.data pipelines, and you can monitor your training in [[TensorBoard]] directly from [[Colaboratory]] and [http://jupyter.org/index.html Jupyter] Notebooks.  [http://cloud.google.com/blog/products/ai-machine-learning/tensorflow-2-0-and-cloud-ai-make-it-easy-to-train-deploy-and-maintain-scalable-machine-learning-models TensorFlow 2.0 and [[Google]] Cloud AI make it easy to train, deploy, and maintain scalable machine learning models | Paige Bailey and Barrett Williams - Google]
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TensorFlow 2.0 focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs, and flexible model building on any platform, tight [[Keras]] integration. You can easily ingest datasets via tf.data pipelines, and you can monitor your training in [[TensorBoard]] directly from [[Colaboratory]] and [http://jupyter.org/index.html Jupyter] Notebooks.  [http://cloud.google.com/blog/products/ai-machine-learning/tensorflow-2-0-and-cloud-ai-make-it-easy-to-train-deploy-and-maintain-scalable-machine-learning-models TensorFlow 2.0 and [[Google]] Cloud AI make it easy to train, deploy, and maintain scalable machine learning models | Paige Bailey and Barrett Williams - Google]
 
  
 
* [http://medium.com/tensorflow/whats-coming-in-tensorflow-2-0-d3663832e9b8 What’s coming in TensorFlow 2.0 | TensorFlow Team - Medium]
 
* [http://medium.com/tensorflow/whats-coming-in-tensorflow-2-0-d3663832e9b8 What’s coming in TensorFlow 2.0 | TensorFlow Team - Medium]
 
* [http://jaxenter.com/ml-tensorflow-2-0-154466.html What’s in store for ML developers in TensorFlow 2.0? | Jane Elizabeth]
 
* [http://jaxenter.com/ml-tensorflow-2-0-154466.html What’s in store for ML developers in TensorFlow 2.0? | Jane Elizabeth]
  
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<youtube>6g4O5UOH304</youtube>
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<youtube>6D7-2JGvFgk</youtube>
 
<youtube>EqWsPO8DVXk</youtube>
 
<youtube>EqWsPO8DVXk</youtube>
 
<youtube>bDZ2q6OktQI</youtube>
 
<youtube>bDZ2q6OktQI</youtube>
 
<youtube>-5LJ77kAYqo</youtube>
 
<youtube>-5LJ77kAYqo</youtube>
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<youtube>jJaG2ytJVQU</youtube>
 
<youtube>b5Rs1ToD9aI</youtube>
 
<youtube>b5Rs1ToD9aI</youtube>
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<youtube>jJaG2ytJVQU</youtube>
 
 
<youtube>WS9Nckd2kq0</youtube>
 
<youtube>WS9Nckd2kq0</youtube>
  
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==== GPU ====
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=== GPU ===
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* [[Processing Units - CPU, GPU, APU, TPU, VPU, FPGA, QPU]]
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* [http://www.youtube.com/results?search_query=GPU+tensorflow Youtube search...]
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<youtube>r7-WPbx8VuY</youtube>
 
<youtube>r7-WPbx8VuY</youtube>
 
<youtube>tCYSce6l8gA</youtube>
 
<youtube>tCYSce6l8gA</youtube>
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<youtube>26t8MfP8Fo0</youtube>
 
  
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==== Code Conversion ====
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=== tf.function ===
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<youtube>JmSNUeBG-PQ</youtube>
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* [http://www.youtube.com/results?search_query=tf.function+tensorflow Youtube search...]
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<youtube>FB0Tlxf4mCs</youtube>
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<youtube>yH1cF7GnoIo</youtube>
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<youtube>Up9CvRLIIIw</youtube>
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=== Eager Execution (Default in 2.0) ====
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* [http://www.youtube.com/results?search_query=eager+execution+tensorflow Youtube search...]
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* [http://towardsdatascience.com/the-roadmap-of-mathematics-for-deep-learning-357b3db8569b Eager Execution vs. Graph Execution in TensorFlow: Which is Better? | Orhan G. Yalcin] ...Comparing Eager Execution and Graph Execution using Code Examples, Understanding When to Use Each and why TensorFlow switched to Eager Execution | Deep Learning with TensorFlow 2.x
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<youtube>T8AW0fKP0Hs</youtube>
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<youtube>yPgvoLWSkFo</youtube>
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 +
=== tf.data - TF Input Pipeline ===
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* [http://www.youtube.com/results?search_query=tf.data+TF+Input+Pipeline+tensorflow Youtube search...]
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<youtube>kVEOCfBy9uY</youtube>
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<youtube>n7byMbl2VUQ</youtube>
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<youtube>uIcqeP7MFH0</youtube>
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<youtube>VeV65oVvoes</youtube>
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=== tf.distribute ===
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* [http://www.youtube.com/results?search_query=tf.distribute+tensorflow Youtube search...]
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<youtube>ZnukSLKEw34</youtube>
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<youtube>jKV53r9-H14</youtube>
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=== mesh-TensorFlow ===
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* [http://www.youtube.com/results?search_query=mesh+tensorflow Youtube search...]
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<youtube>HgGyWS40g-g</youtube>
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<youtube>uPDuJb35bGg</youtube>
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 +
=== TensorFlow Probability ===
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* [http://www.youtube.com/results?search_query=Probability+tensorflow Youtube search...]
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<youtube>BrwKURU-wpk</youtube>
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<youtube>_U-1kJo76o4</youtube>
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=== Reinforcement Learning with TF-Agents ===
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* [http://www.youtube.com/results?search_query=TF-Agents+tensorflow Youtube search...]
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<youtube>-TTziY7EmUA</youtube>
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<youtube>tAOApRQAgpc</youtube>
  
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==== Examples ====
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=== Examples ===
 
<youtube>bNntsCOdFxg</youtube>
 
<youtube>bNntsCOdFxg</youtube>
 
<youtube>HsgyKcC0f_s</youtube>
 
<youtube>HsgyKcC0f_s</youtube>
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<youtube>yXIYD0IeTnw</youtube>
 
<youtube>yXIYD0IeTnw</youtube>
  
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= Prior Version =
 
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== TensorFlow 1.0 ==
 
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<youtube>S9ElPZupUsE</youtube>
 
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<youtube>tYYVSEHq-io</youtube>
 
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<youtube>bYeBL92v99Y</youtube>
 
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<youtube>Hk0yBpCqVRE</youtube>
 
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<youtube>gplTc2F5Wvk</youtube>
 
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<youtube>t81QhHaMS7w</youtube>
 
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<youtube>kSa3UObNS6o</youtube>
 
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<youtube>Rgpfk6eYxJA</youtube>
 
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<youtube>eynHiQm-SUk</youtube>
 
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<youtube>skf35x1lNV4</youtube>
 
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<youtube>Q6ERFwQNkzo</youtube>
 
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<youtube>2FmcHiLCwTU</youtube>
 
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<youtube>qVwm-9P609I</youtube>
 
  
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=== Eager Execution (Default in 2.0) ====
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= Tensorflow for Practice Specialization =
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[http://www.youtube.com/results?search_query=eager+execution+tensorflow Youtube search...]
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 +
* [http://www.coursera.org/specializations/tensorflow-in-practice TensorFlow in Practice Specialization |] [http://www.coursera.org/instructor/lmoroney Laurence Moroney - Coursera]
 +
 
 +
* [http://www.meetup.com/Deep-Learning-Adventures/events/269909321/ Deep Learning Adventures | hosted by George Zoto - Meetup]  
  
−
<youtube>T8AW0fKP0Hs</youtube>
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* Chapter 1:
−
<youtube>yPgvoLWSkFo</youtube>
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** [http://docs.google.com/presentation/d/1GEvlIo8g_OFWWq7S3Ob82wRh5NroXpVSivRvVjFpm4Q/edit?usp=sharing Presentation]
 +
** [http://www.meetup.com/Deep-Learning-Adventures/events/269760835/ Meetup #1 fun-packed event]
 +
** Notes:
 +
*** [http://stats.stackexchange.com/questions/376224/why-map-the-pixel-grayscale-0-1-to-0-01-0-99-before-feeding-to-the-neural Why map the pixel grayscale [0,1] to [0.01, 0.99] before feeding to the neural network?]
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*** [http://machinelearningmastery.com/how-to-normalize-center-and-standardize-images-with-the-imagedatagenerator-in-keras/ How to Normalize, Center, and Standardize Image Pixels in Keras | Jason Brownlee]

Latest revision as of 11:42, 6 November 2024

YouTube ... Quora ...Google search ...Google News ...Bing News



TensorFlow focuses on simplicity and ease of use, with updates like eager execution, intuitive higher-level APIs, and flexible model building on any platform, tight Keras integration. You can easily ingest datasets via tf.data pipelines, and you can monitor your training in TensorBoard directly from Colaboratory and Jupyter Notebooks. TensorFlow 2.0 and Google Cloud AI make it easy to train, deploy, and maintain scalable machine learning models | Paige Bailey and Barrett Williams - Google

GPU

tf.function

Eager Execution (Default in 2.0) =

tf.data - TF Input Pipeline

tf.distribute

mesh-TensorFlow

TensorFlow Probability

Reinforcement Learning with TF-Agents

Examples


Tensorflow for Practice Specialization

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