In a neural network, there is the concept of loss, which is used to calculate performance. The higher the loss, the poorer the performance of the neural network, that is why we always try to minimize the loss so that the neural network performs better.
Neural Style Transfer is a type of algorithm that stylizes the digital image or video by adopting the visual style from another image.
Analyzing the feature importance is necessary for certain predictive analytics works such as credit or loan default predictions
In digital image processing, a lot of various methods are used to increase the quality of the image such as noise reduction, high resolution, etc. Image illumination is one such technique that highly affects the quality of the photo.
CoAtNets is a hybrid model built by Google’s Brain Team and has recently gained the attention of deep learning practitioners.
XAutoML is an analytics tool that explains the AutoML optimization procedures and machine learning pipelines constructed by AutoML.
In this article, we will go through an overview of each of the popular image reconstruction techniques and will understand how these techniques work.
SHAP values (SHapley Additive exPlanations) is an awesome tool to understand your complex Neural network models and other machine learning models such as Decision trees, Random forest.
Colossal-AI is such a powerful system that can perform complicated distributed training and give an easy way to set up different types of parallelism.
Gini impurity is an important measure used to construct the decision trees.
Kubric is an open-source Python framework that allows you to create photo-realistic scenes by combining the functions of PyBullet and Blender.
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