Using Facebook Adaptive Experimentation platform to tune random forest regressors using docker
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Updated
May 10, 2019 - Python
Using Facebook Adaptive Experimentation platform to tune random forest regressors using docker
Modeling of strength of high performance concrete using Machine Learning
The used cars price is predicted using various features - Decision Tree & Random Forest
A simple python interface for running multiple parallel instances of a python program (e.g. gridsearch).
Hyper-Parameter Optimisation experiment as part of my undergraduate dissertation (2019)
Performance predictor with learning curves and meta-features
CLI to create and optimize optuna study without explicit objective function
Predicting if it will rain the next day with clustering and supervised ML
Predicting the Contraceptive Method Choice of a Woman Based on Demographic and Socio-economic Characteristics - The objective of this study is to to predict the contraceptive methods (no use, long-term methods, or short-term methods) of a woman based on her demographic and socio-economic characteristics. A data-set of 1473 married women with the…
Visualized the activations of hidden layers, analyzed feature invariance due to different image alterations and the effects of change in filter-sizes and strides
Data visualization, hypothesis testing and song recommendation with Python
Examples of parameter tuning via DrOpt.
Flight fare perdicting model
The data used in this analysis is an Online Shoppers Purchasing Intention data set provided on the UC Irvine’s Machine Learning Repository. The primary purpose of the data set is to predict the purchasing intentions of a visitor to this particular store’s website. The data set was formed so that each session would belong to a different user in a…
Surrogate adaptive randomized search for hyper-parameters tuning in sklearn.
Efficient and Scalable Batch Bayesian Optimization Using K-Means
Hyper-parameter tuning of Time series forecasting models with Mealpy
Hyper-parameter tuning of classification model with Mealpy
A gradient free optimization routine which combines Particle Swarm Optimization with a local optimization for each particle
Text classification with Machine Learning and Mealpy
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