Difference between revisions of "PRIMO.ai"

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|title=PRIMO.ai
 
|title=PRIMO.ai
 
|titlemode=append
 
|titlemode=append
|keywords=artificial, intelligence, machine, learning, models, algorithms, cybersecurity, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS  
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|keywords=artificial, intelligence, machine, learning, models, algorithms, cybersecurity, data, singularity, moonshot, TensorFlow, Google, NVIDIA, Microsoft, Azure, Amazon, AWS, Facebook
|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; machine learning, videos, articles, techniques, courses, profiles, and tools  
  
 
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-101589255-2"></script>
 
<script async src="https://www.googletagmanager.com/gtag/js?id=UA-101589255-2"></script>
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*** [[Benchmarks]]
 
*** [[Benchmarks]]
 
*** [[Data Preprocessing]]
 
*** [[Data Preprocessing]]
**** [[Feature Exploration/Learning]] ...inspection, data profiling, selection
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**** [[Feature Exploration/Learning]]  
**** [[Data Quality]] ...[[AI Verification and Validation|validity]], accuracy, [[Data Quality#Data Cleaning|cleaning]], completeness, consistency, uniformity, [[Data Quality#Data Encoding|encoding]], [[Data Quality#Zero Padding|padding]],   [[Data Quality#Data Augmentation, Data Labeling, and Auto-Tagging|augmentation, labeling, auto-tagging]], [[Data Quality#Batch Norm(alization) & Standardization| normalization, standardization]], and [[Data Quality#Imbalanced Data|imbalanced data]]  
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**** [[Data Quality]] ...[[AI Verification and Validation|validity]], [[Evaluation - Measures#Accuracy|accuracy]], [[Data Quality#Data Cleaning|cleaning]], [[Data Quality#Data Completeness|completeness]], [[Data Quality#Data Consistency|consistency]], [[Data Quality#Data Encoding|encoding]], [[Data Quality#Zero Padding|padding]], [[Data Quality#Data Augmentation, Data Labeling, and Auto-Tagging|augmentation, labeling, auto-tagging]], [[Data Quality#Batch Norm(alization) & Standardization| normalization, standardization]], and [[Data Quality#Imbalanced Data|imbalanced data]]  
 
*** [[Bias and Variances]]
 
*** [[Bias and Variances]]
*** [[Master Data Management (MDM) / Feature Store / Data Lineage / Data Catalog]]
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*** [[Algorithm Administration#Master Data Management (MDM)|Master Data Management (MDM)]]
 
**** [[Natural Language Processing (NLP)#Managed Vocabularies |Managed Vocabularies]]
 
**** [[Natural Language Processing (NLP)#Managed Vocabularies |Managed Vocabularies]]
 
**** [[Datasets]]  
 
**** [[Datasets]]  
*** [[Privacy in Data Science]]
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*** [[Privacy]] in Data Science
 
*** [[Data Interoperability]]
 
*** [[Data Interoperability]]
 
*** [[Excel - Data Analysis]]
 
*** [[Excel - Data Analysis]]
 
* [[Visualization]]
 
* [[Visualization]]
* [[Hyperparameter]]s
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* [[Algorithm Administration#Hyperparameter|Hyperparameter]]s
 
* [[Evaluation]]
 
* [[Evaluation]]
 
** [[Evaluation - Measures]]
 
** [[Evaluation - Measures]]
 
* [[Train, Validate, and Test]]
 
* [[Train, Validate, and Test]]
= [[Algorithms]] =
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= <span id="Algorithms"></span>[[Algorithms]] =
 +
* [[Algorithms]]; the engines of AI
 
* [[Model Zoos]]
 
* [[Model Zoos]]
 
* [[Graphical Tools for Modeling AI Components]]
 
* [[Graphical Tools for Modeling AI Components]]
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* [[Lasso Regression]]
 
* [[Lasso Regression]]
 
* [[Elastic Net Regression]]
 
* [[Elastic Net Regression]]
* [[Bayesian Linear Regression]]
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* [[Bayes#Bayesian Linear Regression|Bayesian Linear Regression]]
* [[Bayesian Deep Learning (BDL)]]
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* [[Bayes#Bayesian Deep Learning (BDL)|Bayesian Deep Learning (BDL)]]
 
* [[Logistic Regression (LR)]]
 
* [[Logistic Regression (LR)]]
 
* [[Support Vector Regression (SVR)]]
 
* [[Support Vector Regression (SVR)]]
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== Classification [[...predict categories]] ==
 
== Classification [[...predict categories]] ==
 
* <span id="Supervised"></span>[[Supervised]]
 
* <span id="Supervised"></span>[[Supervised]]
** [[Naive Bayes]]
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** Naive [[Bayes]]
 
** [[K-Nearest Neighbors (KNN)]]
 
** [[K-Nearest Neighbors (KNN)]]
 
** [[Perceptron (P)]] ...and Multi-layer Perceptron (MLP)
 
** [[Perceptron (P)]] ...and Multi-layer Perceptron (MLP)
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* [[Neural Structured Learning (NSL)]]
 
* [[Neural Structured Learning (NSL)]]
  
== Sequence / Time ==
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== Sequence / [[Time]] ==
 
* [[Transformer]]
 
* [[Transformer]]
 
** [[Generative Pre-trained Transformer (GPT)]]
 
** [[Generative Pre-trained Transformer (GPT)]]
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* [[(Tree) Recursive Neural (Tensor) Network (RNTN)]]
 
* [[(Tree) Recursive Neural (Tensor) Network (RNTN)]]
  
=== Time ===
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=== [[Time]] ===
 
* [[Temporal Difference (TD) Learning]]
 
* [[Temporal Difference (TD) Learning]]
 
* Predict values
 
* Predict values
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= Techniques =
 
= Techniques =
 
* [[Math for Intelligence]]
 
* [[Math for Intelligence]]
** [[Statistics for Intelligence]]
 
 
** [[Finding Paul Revere]]
 
** [[Finding Paul Revere]]
 
* [http://www.arxiv-sanity.com/ Arxiv Sanity Preserver] to accelerate research
 
* [http://www.arxiv-sanity.com/ Arxiv Sanity Preserver] to accelerate research
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=== Methods & Concepts ===
 
=== Methods & Concepts ===
 
* [[Backpropagation]]
 
* [[Backpropagation]]
 +
* [[Gradient Descent Optimization & Challenges|Stochastic Gradient Descent]]
 +
* [[Gradient Descent Optimization & Challenges#Learning Rate Decay|Learning Rate Decay]]
 +
* [[Pooling / Sub-sampling: Max, Mean|Max Pooling]]
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* [[Data Quality#Batch Norm(alization) & Standardization|Batch Normalization]]
 
* [[Overfitting Challenge]]
 
* [[Overfitting Challenge]]
 
** [[Regularization]]
 
** [[Regularization]]
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* [[Deep Features]]  
 
* [[Deep Features]]  
 
* [[Local Features]]
 
* [[Local Features]]
* [[Human in the Loop]]
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* [[Loop#Unintended Feedback Loop|Unintended Feedback Loop]]
 +
* [[Backtesting]]
  
=== [[Learning Techniques]] ===
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=== <span id="Learning Techniques"></span>[[Learning Techniques]] ===
* [[Text Transfer Learning]]  
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* [[PRIMO.ai#Supervised|Supervised Learning]]
* [[Image/Video Transfer Learning]]
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* [[PRIMO.ai#Unsupervised|Unsupervised Learning]]
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* [[PRIMO.ai#Reinforcement Learning (RL)|Reinforcement Learning (RL)]]
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* [[PRIMO.ai#Semi-Supervised|Semi-Supervised Learning]]
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* [[PRIMO.ai#Self-Supervised|Self-Supervised Learning]]
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* [[Deep Learning]]
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* [[Transfer Learning]] a model trained on one task is re-purposed on a second related task
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** [[Text Transfer Learning]]  
 +
** [[Image/Video Transfer Learning]]
 
* [[Few Shot Learning]]
 
* [[Few Shot Learning]]
* [[Transfer Learning]] a model trained on one task is re-purposed on a second related task
 
 
* [[Ensemble Learning]]
 
* [[Ensemble Learning]]
 
* [[Multi-Task Learning (MTL)]]
 
* [[Multi-Task Learning (MTL)]]
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* [[Neural Structured Learning (NSL)]]
 
* [[Neural Structured Learning (NSL)]]
 
* [[Meta-Learning]]
 
* [[Meta-Learning]]
* [[Human-in-the-Loop Learning]]
+
* [[Online Learning]]
 +
* [[Human-in-the-Loop (HITL) Learning]] / Active Learning
 +
* [[Decentralized: Federated & Distributed]] Learning
  
 
=== Opportunities & Challenges ===
 
=== Opportunities & Challenges ===
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** [[Capsule Networks (CapNets)]]  
 
** [[Capsule Networks (CapNets)]]  
 
** [[Messaging & Routing]]  
 
** [[Messaging & Routing]]  
** [[Federated]] Learning
 
** [[Distributed]] Learning
 
 
** [[Processing Units - CPU, GPU, APU, TPU, VPU, FPGA, QPU]]
 
** [[Processing Units - CPU, GPU, APU, TPU, VPU, FPGA, QPU]]
 
* [[Integrity Forensics]]
 
* [[Integrity Forensics]]
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* [[Quantum]]
 
* [[Quantum]]
  
= Development & Implementation =
+
= <span id="Development & Implementation"></span>Development & Implementation =
 
* [[Building Your Environment]]
 
* [[Building Your Environment]]
* [[AIOps / MLOps]]
+
* [[Algorithm Administration]]
 +
** [[Algorithm Administration#AIOps / MLOps|AIOps / MLOps]]
 
* [[Service Capabilities]]
 
* [[Service Capabilities]]
 
* [[AI Marketplace & Toolkit/Model Interoperability]]
 
* [[AI Marketplace & Toolkit/Model Interoperability]]
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== No Coding ==
 
== No Coding ==
* [[Automated Machine Learning (AML) - AutoML]]
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* [[Algorithm Administration#Automated Learning|Automated Learning]]
 
* [[Neural Architecture]] Search (NAS) Algorithm
 
* [[Neural Architecture]] Search (NAS) Algorithm
 
* [[Other codeless options, Code Generators, Drag n' Drop]]
 
* [[Other codeless options, Code Generators, Drag n' Drop]]
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=== Tooling ===
 
=== Tooling ===
 
* [[Model Search]]
 
* [[Model Search]]
* [[Model Monitoring]]
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* [[Algorithm Administration#Model Monitoring|Model Monitoring]]
 
* [[Notebooks]]; [[Jupyter]] and R Markdown
 
* [[Notebooks]]; [[Jupyter]] and R Markdown
  
=== [[Platforms: Machine Learning as a Service (MLaaS)]] ===
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=== [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)]] ===
 
* [[Google]] Cloud Platform (GCP)
 
* [[Google]] Cloud Platform (GCP)
 
* [[Amazon]] AWS  
 
* [[Amazon]] AWS  
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<hr>
 
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[http://www.etsy.com/shop/LittleHouseOnTheBay Little House On The Bay Soaps]
 
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<hr>
  
  
  
 
If you get a 502 or 503 error please try the webpage again, as your message is visiting the island which the server is located, perhaps deciding to relax in the Sun before returning. Thank you.
 
If you get a 502 or 503 error please try the webpage again, as your message is visiting the island which the server is located, perhaps deciding to relax in the Sun before returning. Thank you.

Revision as of 22:41, 1 December 2020

On Friday March 29, 2024 PRIMO.ai has 733 pages

Getting Started

Overview

Background

AI Breakthroughs

AI Fun

.. more Natural Language Processing (NLP) fun...

How to...

Forward Thinking

Information Analysis

Algorithms

Predict values - Regression

Classification ...predict categories

Recommendation

Clustering - Continuous - Dimensional Reduction

Hierarchical

Convolutional

Deconvolutional

Graph

- includes social networks, sensor networks, the entire Internet, 3D Objects (Point Cloud)

Sequence / Time

Time

Spatialtemporal

Spatial-Temporal Dynamic Network (STDN)

Competitive

Semi-Supervised

In many practical situations, the cost to label is quite high, since it requires skilled human experts to do that. So, in the absence of labels in the majority of the observations but present in few, semi-supervised algorithms are the best candidates for the model building. These methods exploit the idea that even though the group memberships of the unlabeled data are unknown, this data carries important information about the group parameters. Reference: Learning Techniques

Natural Language

  • Natural Language Processing (NLP) involves speech recognition, (speech) translation, understanding (semantic parsing) complete sentences, understanding synonyms of matching words, and sentiment analysis

Reinforcement Learning (RL)

an algorithm receives a delayed reward in the next time step to evaluate its previous action. Therefore based on those decisions, the algorithm will train itself based on the success/error of output. In combination with Neural Networks it is capable of solving more complex tasks. Policy Gradient (PG) methods are a type of reinforcement learning techniques that rely upon optimizing parametrized policies with respect to the expected return (long-term cumulative reward) by gradient descent.

Neuro-Symbolic

the “connectionists” seek to construct artificial neural networks, inspired by biology, to learn about the world, while the “symbolists” seek to build intelligent machines by coding in logical rules and representations of the world. Neuro-Symbolic combines the fruits of group.

Other

Techniques

Methods & Concepts

Learning Techniques

Opportunities & Challenges

Development & Implementation

No Coding

Coding

Libraries & Frameworks

TensorFlow

Tooling

Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)

... and other leading organizations



Little House On The Bay Soaps



If you get a 502 or 503 error please try the webpage again, as your message is visiting the island which the server is located, perhaps deciding to relax in the Sun before returning. Thank you.