Skip to main content

CPU Model in Linux

 Ever wondered what kind of CPU model you are using in Linux? This command will pull it up:

gcc -march=native -Q --help=target|grep march

Popular posts from this blog

AI Key Terms and Concepts Notes

Mere notes Model: A mathematical representation of a problem, situation, phenomenon, or process Training: The process of using an algorithm to create a model from a set of data Training Set: A subset of our ground truth data that our model will learn from Algorithm: A procedure, or set of steps Machine learning (probabilistic approach) vs Rules-based system If the universe of possible outcomes is well delineated then stick with rules. Purpose of Ground Truth Data Ground truth data helps many learning systems to learn and evaluate their own performance by providing a gold standard on what the truth actually is. Source: Udacity AI for Business Leaders
Read more

Supervised, Unsupervised, Semi-supervised, and Reinforcement Learning

 https://blogs.nvidia.com/blog/2018/08/02/supervised-unsupervised-learning/  Source: Udacity AI for Business Leaders Supervised Learning - A category of machine learning which relies on the proper values, or labels , being present for the output data in the ground truth dataset, which the model can “learn” from during its training process. Labels - Values of the output variable/column/piece of data you are interested in Unsupervised Learning - A category of machine learning which uses the underlying characteristics of data itself, rather than already-supplied labels for outputs, to inform the model’s training process. Often uses segmenting or clustering algorithms to determine the output values. Reinforcement Learning - A category of machine learning which uses a series of simulations/cycles to reward optimal behaviors to learn policies for decision making in complex scenarios such as autonomous driving.
Read more