PerfAvore VS Bayesian-Optimization-in-FSharp

Compare PerfAvore vs Bayesian-Optimization-in-FSharp and see what are their differences.

PerfAvore

Rule based performance analysis and monitoring tool for dotnet written in F#. (by MokoSan)
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PerfAvore Bayesian-Optimization-in-FSharp
1 1
13 5
- -
0.0 10.0
over 2 years ago over 1 year ago
Jupyter Notebook Jupyter Notebook
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

PerfAvore

Posts with mentions or reviews of PerfAvore. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-12-20.

Bayesian-Optimization-in-FSharp

Posts with mentions or reviews of Bayesian-Optimization-in-FSharp. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing PerfAvore and Bayesian-Optimization-in-FSharp you can also consider the following projects:

pcm - IntelĀ® Performance Counter Monitor (IntelĀ® PCM)

BayesianOptimization - A Python implementation of global optimization with gaussian processes.

ionide-vscode-fsharp - VS Code plugin for F# development

Spotify_Song_Recommender - This project leverages spotify's api and provided user playlists to create and tune a neural network model that generates song recommendations based off of song data in provided playlists.

realmon - A monitoring tool that tells you when GCs happen in a process and some characteristics about these GCs

neural-tangents - Fast and Easy Infinite Neural Networks in Python

mango - Parallel Hyperparameter Tuning in Python

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.

Intrusion-Detection-System-Using-Machine-Learning - Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)