PRIMO.ai

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On Saturday September 23, 2023 PRIMO.ai has 715 pages

Primo.ai provides links to articles and videos on Artificial intelligence (AI) concepts and techniques such as Generative AI, Natural Language Processing (NLP), Computer Vision, Deep Learning, Reinforcement Learning (RL), and Quantum Technology. It is a resource for individuals who are passionate about learning and developing new skills.

Getting Started

AI Fun

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

How to...

Forward Thinking



Generative AI (Gen AI)

The ability to generate new content or solutions, such as writing or designing new products, using techniques such as Generative Adversarial Network (GAN) or neural style transfer.



Information Analysis

Algorithms

Predict values - Regression

Analyze large amounts of data and make predictions or recommendations based on that data.

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-based Algorithms

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

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

Policy

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



Sponsored by... Little House On The Bay



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