deephyper
keras-tuner
| deephyper | keras-tuner | |
|---|---|---|
| 1 | 4 | |
| 262 | 2,827 | |
| 0.8% | 0.6% | |
| 8.9 | 7.8 | |
| 12 days ago | about 1 month ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
deephyper
-
[R] DeepHyper; software package to automate design and development of ML models
Link: https://github.com/deephyper/deephyper
keras-tuner
- Is there any premade evolutionary algorithm selecting optimal NN architectures in TensorFlow ?
-
What has priority in the performance?
If you are using tensorflow, you can do all of that with the very elegant (in my opinion) https://keras.io/keras_tuner/
-
Space Science with Python - Asteroids meet Deep Learning #10
today I'd like to show you how to optimize a Conv1D network using Keras-Tuner. It enables one to automatically test some pre-defined networks; or it applies Bayesian or Hyperband optimization to find the best model!
-
How to know how many layers (LSTM and dense) should I create and how to know the right parameters? (beginner)
Tbh, just try and error. There is no right or wrong. You can use the Hyperparameter Tuner from keras to define some architectures with varying number of layers and units as well as some other hyperparameters.
What are some alternatives?
autokeras - AutoML library for deep learning
Ray - Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
wandb - 🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.
vizier - Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
archai - Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
openrec - OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
compression - Data compression in TensorFlow
ml-engineering - Machine Learning Engineering Open Book