Utility functions for hyperparameter optimization using hyperopt, especially from Jupyter notebooks.

The jupyter notebooks of the deep learning specialization by deeplearning.ai

Two Jupyter Notebooks written in Python, treating of time series analysis with ARIMA and its seasonal counterpart.

5 courses of Specialization in Deep Learning taught by Prof.Andrew Ng on Coursera

Topic modelling - optimization of model hyper params. Notebooks are examples of using our optimization pipeline for sample data.

Jupyter Notebook Templates for quick prototyping of machine learning solutions

Bayesian Optimization for hyperparameter tuning in machine learning using a Jupyter Notebook. This repository demonstrates optimizing a Gradient Boosting Classifier with practical examples and clear explanations.

This notebook explores comprehensive machine learning analysis on a rock dataset, covering attribute distribution analysis, outlier identification using statistical values and visualizations like scatter plots,and applying Multinomial Logistic Regression,Support Vector Machines, Random Forest classifiers,Ensemble learning,hyperparameter optimizatio

This is a notebook which uses keras tuner to optimize the hyperparameters of a model on CIFAR-10.

This repository contains programming assignments for the Deep Learning Specialization by deeplearning.AI. It includes Jupyter Notebooks for exercises in neural networks, hyperparameter tuning, convolutional networks, and sequence models.

This repository contains demo notebooks (sample code) for the AutoMLx (automated machine learning and explainability) package from Oracle Labs.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle