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38 search results found

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

Wandb ⭐ 8,204

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

Skypilot ⭐ 4,975

SkyPilot: Run LLMs, AI, and Batch jobs on any cloud. Get maximum savings, highest GPU availability, and managed execution—all with a simple interface.

Determined ⭐ 2,715

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

Forecasting ⭐ 2,540

Time Series Forecasting Best Practices & Examples

Coursera Deep Learning Specialization ⭐ 2,459

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered 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 Networks; (v) Sequence Models

Talos ⭐ 1,596

Hyperparameter Optimization for TensorFlow, Keras and PyTorch

Vizier ⭐ 1,142

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

Hyperparameter Optimization Of Machine Learning Algorithms ⭐ 1,025

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

Onepanel ⭐ 707

The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.

Hyperparameter_hunter ⭐ 635

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

Neuraxle ⭐ 533

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

Agilerl ⭐ 457

Streamlining reinforcement learning with RLOps

Automl Implementation For Static And Dynamic Data Analytics ⭐ 443

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

Hyperboard ⭐ 327

A web-based dashboard for Deep Learning

Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.

Deeplearning.ai Notes ⭐ 271

These are my notes which I prepared during deep learning specialization taught by AI guru Andrew NG. I have used diagrams and code snippets from the code whenever needed but following The Honor Code.

Auptimizer ⭐ 195

An automatic ML model optimization tool.

Adatune ⭐ 144

Gradient based Hyperparameter Tuning library in PyTorch

Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.

Population Based Training (in PyTorch with sqlite3). Status: Unsupported

Metadata store for Production ML

Pre-trained Gaussian processes for Bayesian optimization

Clsurvey ⭐ 61

Continual Hyperparameter Selection Framework. Compares 11 state-of-the-art Lifelong Learning methods and 4 baselines. Official Codebase of "A continual learning survey: Defying forgetting in classification tasks." in IEEE TPAMI.

Hypertune ⭐ 60

A library for performing hyperparameter optimization

Mindware ⭐ 54

An efficient open-source AutoML system for automating machine learning lifecycle, including feature engineering, neural architecture search, and hyper-parameter tuning.

The Deep Learning With Keras Workshop ⭐ 40

An Interactive Approach to Understanding Deep Learning with Keras

Cerebro System ⭐ 18

Data System for Optimized Deep Learning Model Selection

Nlpboost ⭐ 14

Python library for automatic training, optimization and comparison of Transformer models on most NLP tasks.

GUI for Keras and TensorFlow with integrated hyperparameter optimization and NLP

Cs230_dl ⭐ 13

♊ Stanford CS230 : Deep Learning

Hypernomad ⭐ 10

A library for the hyperparameter optimization of deep neural networks

[NeurIPS 2023] Multi-fidelity hyperparameter optimization with deep power laws that achieves state-of-the-art results across diverse benchmarks.

Deeplearning.ai Deep Learning Specialization ⭐ 9

This repo contains my work & The code base for this Deep Learning Specialization offered by deeplearning.AI

Neural Networks And Deep Learning ⭐ 9

Deep learning projects including applications (face recognition, neural style transfer, autonomous driving, sign language reading, music generation, translation, speech recognition and NLP) and theories (CNNs, RNNs, LSTM, Adam, Dropout, BatchNorm, Xavier/He initialization, hyperparameter tuning, regularization, optimization, Residual Networks). Deep Learning Specialization by Andrew Ng, deeplearning.ai

Pytorch Rnn Tutorial ⭐ 9

PyTorch tutorial for using RNN and Encoder-Decoder RNN for time series forecasting

Prediction Of Solar Radiation ⭐ 9

Utilizing an Artificial Neural Network (ANN) based on Hyperparameter tuning, a new solution for Solar Radiation is approached.

Deep Learning Specialization ⭐ 8

This repository contains the programming assignments and slides from the deep learning course from coursera offered by deeplearning.ai

Coursera Deep Learning Specialization ⭐ 7

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered 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 Networks..

Hyperparameter Tuning In Matlab Using Experiment Manager And Tensorflow ⭐ 7

This example shows how to use MATLAB to train a TensorFlow model and tune it's hyperparameters using co-execution with Python.

Scalable Hpo Pybay ⭐ 5

This repositorty will contain the code and slides for PyBay2020 talk: Scalable Hyper-parameter Optimization using RAPIDS and AWS

Neurosymbolic Tinyml ⭐ 5

TinyNS: Platform-Aware Neurosymbolic Auto Tiny Machine Learning

Machine Learning Toolbox 2

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1-38 of 38 search results

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