📘 The MLOps stack component for experiment tracking
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Updated
Jul 9, 2024 - Python
📘 The MLOps stack component for experiment tracking
Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
Python library for CMA Evolution Strategy.
ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) methods. The supported algorithms in this application are Neural Networks, Random Forests & Ensembl Models.
Free trading system for crypto exchanges SPOT market. Adaptive customizable reverse grid strategy based on martingale.
Make GNN easy to start with
PyTorch-Lightning Library for Neural News Recommendation
⚡️ AllenNLP plugin for adding subcommands to use Optuna, making hyperparameter optimization easy
OptKeras: wrapper around Keras and Optuna for hyperparameter optimization
Train, evaluate, and optimize implicit feedback-based recommender systems.
Example codes in the medium post titled "Optuna meets Weights and Biases."
Trying PostgreSQL parameter tuning using machine learning.
Tools for Optuna, MLflow and the integration of both.
Python library and dashboard for hyperparameter search and model training for computer vision tasks based on PyTorch, Optuna, FiftyOne, Dash, Segmentation Model Pytorch.
A game search and evaluation parameter tuner using optuna framework
Building and evaluating a ranking model using the MSLR-WEB10K dataset
Hyperparameter optimization study for a PyTorch CNN with Optuna.
zero-code hyperparameters optimization framework
🥈42nd place in CommonLit Readability Prize competition🥈
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