Hyperparameter-tuning Libraries

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Hyperparameter-tuning Libraries

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

To install the current release: Participating discussions via the following IM groups is also welcomed. Over the past few years, NNI has received thousands of feedbacks on GitHub issues, and pull req…

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Get started with W&B in four steps: That's it! Navigate to the W&B App to view a dashboard of your first W&B Experiment. Use the W&B App to compare multiple experiments in a unified…

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production models. Flexible integration for any Python script: Build …

Easy hyperparameter optimization and automatic result saving across machine learning algorithms and libraries

Automatically save and learn from Experiment results, leading to long-term, persistent optimization that remembers all your tests. HyperparameterHunter provides a wrapper for machine learning algorit…

State-of-the art Automated Machine Learning python library for Tabular Data

Classifier: Regression: DataPrepare: Simple Models Wrapper: More examples in the folder ./examples: It integrates many popular frameworks: Run

Implementation of Logistic Regression, MLP, CNN, RNN & LSTM from scratch in python. Training of deep learning models for image classification, object detection, and sequence processing (including transformers implementation) in TensorFlow.

The solutions uploaded in this repository are only for reference when you got stuck somewhere. Please don't use these solutions to pass programming assignments.

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