A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. arXiv:2307.09218.
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Updated
Jun 20, 2024
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning. arXiv:2307.09218.
Developer Version of the R package CAST: Caret Applications for Spatio-Temporal models
Reducing overfitting in perdiction in decision trees
Classification between pet images using different approaches on famous cats vs dogs dataset available on kaggle.
Content: Classification, Sigmoid function, Decision Boundary, Cost function, Gradient descent, Overfitting, Regularisation
Predicting various emotion in human speech signal by detecting different speech components affected by human emotion.
Machine Learning: Regression and Classification. Andrew presents a course in introduction to machine learning, with practice in regression and classification for the first and second course, and the third course focuses on recommender systems and reinforcement learning.
We explore the Titanic Kaggle competition, employing advanced analytics and machine learning to accurately predict survival rates. This repository serves as a detailed guide for all levels, offering visual insights, data preprocessing methods, and model comparisons.
PyTorch code for FLD (Feature Likelihood Divergence), FID, KID, Precision, Recall, etc. using DINOv2, InceptionV3, CLIP, etc.
Overfitting is often caused by using a model with too many parameters or if the model is too powerful for the given dataset. On the other hand, underfitting is often caused by the model with too few parameters or by using a model that is not powerful enough for the given dataset. In this we are discussing about that.
Supervised Learning - Regression Algorithm
Package with data, scripts and plots for manuscript "A comparison of machine learning and statistical species distribution models: when overfitting hurts interpretation" (submitted to Ecological Modelling, Dec 2022)
Xinshao Wang, Ex-Postdoc and Ex-Visit Scholar@University of Oxford, Ex-Senior Researcher@ZenithAI
spatial resampling for more robust cross validation in spatial studies
Introduction of system identification on an unkown plant with various models.
Machine Learning: model optimization through hyperparameters
Machine Learning Course [ECE 501] - Spring 2023 - University of Tehran - Dr. A. Dehaqani, Dr. Tavassolipour
Series of tutorials from Resolving Python on how to compute different algorithms for predicting the future based on tabular data.
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