Data visualization, hypothesis testing and song recommendation with Python
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Updated
Jan 15, 2024 - Jupyter Notebook
Data visualization, hypothesis testing and song recommendation with Python
DataFrame support for scikit-learn.
Nature-inspired algorithms for hyper-parameter tuning of Scikit-Learn models.
Graded assignments of all the courses that are being offered in Coursera Deep Learning Specialization by DeepLearning.AI. (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Network (v) Squence Model
A gradient free optimization routine which combines Particle Swarm Optimization with a local optimization for each particle
CLI to create and optimize optuna study without explicit objective function
Hyper-parameter tuning of Time series forecasting models with Mealpy
Text classification with Machine Learning and Mealpy
Hyper-parameter tuning of classification model with Mealpy
The used cars price is predicted using various features - Decision Tree & Random Forest
Flight fare perdicting model
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…
A simple python interface for running multiple parallel instances of a python program (e.g. gridsearch).
Visualized the activations of hidden layers, analyzed feature invariance due to different image alterations and the effects of change in filter-sizes and strides
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…
Examples of parameter tuning via DrOpt.
Performance predictor with learning curves and meta-features
Modeling of strength of high performance concrete using Machine Learning
Predicting if it will rain the next day with clustering and supervised ML
Surrogate adaptive randomized search for hyper-parameters tuning in sklearn.
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