hyperopt

Rikj000/MoniGoMani

Isn't that what we all want? Our money to go many? Well that's what this framework/strategy hopes to do for you! By giving you & HyperOpt a lot of signals to alter the weights from.

flytxtds/AutoGBT

AutoGBT is used for AutoML in a lifelong machine learning setting to classify large volume high cardinality data streams under concept-drift. AutoGBT was developed by a joint team ('autodidact.ai') from Flytxt, Indian Institute of Technology Delhi and CSIR-CEERI as a part of NIPS 2018 AutoML for Lifelong Machine Learning Challenge.

solegalli/hyperparameter-optimization

Code repository for the online course Hyperparameter Optimization for Machine Learning

jrzaurin/ml-pipeline

Using Kafka-Python to illustrate a ML production pipeline

auto-flow/ultraopt

Distributed Asynchronous Hyperparameter Optimization better than HyperOpt. 比HyperOpt更强的分布式异步超参优化库。

guillaume-chevalier/Hyperopt-Keras-CNN-CIFAR-100

Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.

dnkirill/allstate_capstone

Allstate Kaggle Competition ML Capstone Project

atanasster/hyperparameters

ES6 hyperparameters search for tfjs

JonnoFTW/traffic-prediction

Predict traffic flow with LSTM. For experimental purposes only, unsupported!

ml-tooling/lazycluster

🎛 Distributed machine learning made simple.

aldente0630/mofc-demand-forecast

Time Series Forecasting for the M5 Competition

ISG-Siegen/Auto-Surprise

An AutoRecSys library for Surprise. Automate algorithm selection and hyperparameter tuning :rocket:

PhilipMay/mltb

Machine Learning Tool Box

nphdang/Bandit-BO

Bayesian Optimization for Categorical and Continuous Inputs

abhishekdbihani/Home-Credit-Default-Risk-Recognition

The project provides a complete end-to-end workflow for building a binary classifier in Python to recognize the risk of housing loan default. It includes methods like automated feature engineering for connecting relational databases, comparison of different classifiers on imbalanced data, and hyperparameter tuning using Bayesian optimization.

Apaezmx/simplifai

Free automated deep learning for spreadsheets

Davisy/Hyperparameter-Optimization-Techniques

Different hyperparameter optimization methods to get best performance for your Machine Learning Models

EsterHlav/Quantitative-Comparison-NLP-Embeddings-from-GloVe-to-RoBERTa

Fair quantitative comparison of NLP embeddings from GloVe to RoBERTa with Sequential Bayesian Optimization fine-tuning using Flair and SentEval. Extension of HyperOpt library to log_b priors.

raphant/lazyft

A convenient FreqTrade wrapper-library that makes it easy to develop algorithmic trading strategies.

himanshurawlani/hyper_fcn

Hyperparameter tuning for FCN using Ray Tune

renardeinside/e2e-mlops-demo

E2E MLOps with Databricks

genfifth/cvopt

Machine learning's parameter search and feature selection module which is integrated log management and visualization.

njnmco/hopticulate

Reticulate wrapper for hyperopt

yassineAlouini/hyperparameters-optimization

The accompanying repo for the hyperparameters optimization bdx meetup talk, blog post and webinar

MahtabShaan/autoencoder-as-feature-extractor-CIFAR-10

CIFAR-10 image classification of imbalanced data using bottleneck features extracted from the autoencoder.

PaulEmmanuelSotir/NYC_TaxiTripDuration

NYC taxi trip duration Kaggle submission using fully connected neural network

ArpanSM/Machine_Learning_Hackathons

Machine learning and Deep Learning Hackathon Solutions

asreview/asreview-hyperopt

Hyper parameter optimization extension for ASReview. EXPERIMENTAL

databricks-industry-solutions/rare-event-inspection

Kakapo (KAH-kə-poh) implements a standard set of APIs for outlier detection at scale on Databricks. It provides an integration of the vast PyOD library of outlier detection algorithms with MLFlow for tracking and packaging of models and hyperopt for exploring vast, complex and heterogeneous search spaces.

farazmah/hyperparameter

Hyperparameter optimisation utility for lightgbm and xgboost using hyperopt.

MBKraus/Hyperopt

Repo that relates to the Medium blog 'Using Bayesian Optimization to reduce the time spent on hyperparameter tuning'

gulabpatel/Hyper_Parameter_Optimization

We will discuss the Hyper Parameter Tuning for different Machine Learning Algorithm

Yyalexx/Predict-a-biological-response

yaroslav-vorobyov/SF_DST

Data Science Professional course

Yyalexx/SF-homeworks