|6 days ago||6 days ago|
|Apache License 2.0||MIT License|
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.
[D] Tips for ML workflow on raw data
2 projects | reddit.com/r/MachineLearning | 21 Jan 2022
Machine Learning adventures with MLFlow - Deploying models from local system to Production
1 project | reddit.com/r/learnmachinelearning | 22 Dec 2021
Its a bug with mlflow -> https://github.com/mlflow/mlflow/issues/3755 Keep the server on, open another terminal export MLFLOW_TRACKING_URI env variable, if on windows set the env variable.....should work.
Old guy programmer here, need to brush up on Python quickly!
13 projects | reddit.com/r/Python | 6 Dec 2021
mlflow for logging and visualizing ML model experiments
Taking on the ML pipeline challenge: why data scientists need to own their ML workflows in production
4 projects | dev.to | 6 Dec 2021
So, if you even want to use MLFlow to track your experiments, run the pipeline on Airflow, and then deploy a model to a Neptune Model Registry, ZenML will facilitate this MLOps Stack for you. This decision can be made jointly by the data scientists and engineers. As ZenML is a framework, custom pieces of the puzzle can also be added here to accommodate legacy infrastructure.
[D] 5 considerations for Deploying Machine Learning Models in Production – what did I miss?
3 projects | reddit.com/r/MachineLearning | 21 Nov 2021
Consideration Number #2: Consider using model life cycle development and management platforms like MLflow, DVC, Weights & Biases, or SageMaker Studio. And Ray, Ray Tune, Ray Train (formerly Ray SGD), PyTorch and TensorFlow for distributed, compute-intensive and deep learning ML workloads.
[P] DagYard - DVC x MLflow x Colab x Gdrive - Automatically Configured
2 projects | reddit.com/r/MachineLearning | 18 Nov 2021
MLflow tracking automates the logging process of experiments and sends live information to a local or remote server while the training is still running.
Data Science toolset summary from 2021
13 projects | dev.to | 13 Nov 2021
MLflow - https://mlflow.org/
How to store preprocessing and feature engineering pipeline?
1 project | reddit.com/r/datascience | 21 Oct 2021
MLOps project based template
4 projects | reddit.com/r/mlops | 11 Oct 2021
ML workflow - MLflow
[D] Facebook Visdom vs Google Tensorboard for Pytorch
5 projects | reddit.com/r/MachineLearning | 26 Sep 2021
Oh I think most of the paid tracking solutions have auto refresh. As for the free ones? At clear.ml we have them for quite a while, for MLflow there is an open feature request. https://github.com/mlflow/mlflow/issues/2099
Uber Releases V1.1 of Orbit: A Python Package to Perform Bayesian Time-Series Analysis and Forecasting
1 project | reddit.com/r/Python | 15 Jan 2022
prophet: NEW Data - star count:13871.0
1 project | reddit.com/r/algoprojects | 8 Jan 20221 project | reddit.com/r/algoprojects | 7 Jan 20221 project | reddit.com/r/algoprojects | 6 Jan 20221 project | reddit.com/r/algoprojects | 5 Jan 20221 project | reddit.com/r/algoprojects | 4 Jan 20221 project | reddit.com/r/algoprojects | 3 Jan 20221 project | reddit.com/r/algoprojects | 2 Jan 2022
Time series analysis of Bitcoin price in Python with fbprophet ?!
2 projects | dev.to | 22 Dec 2021
[Q] How would you forecast trend of a time series based on external regressors?
1 project | reddit.com/r/statistics | 21 Dec 2021
This could be a good use case for Facebook Prophet. I’ve been using it for a few years. Some things I love:
What are some alternatives?
tensorflow - An Open Source Machine Learning Framework for Everyone
Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
scikit-learn - scikit-learn: machine learning in Python
dvc - 🦉Data Version Control | Git for Data & Models | ML Experiments Management
greykite - A flexible, intuitive and fast forecasting library
clearml - ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
zenml - ZenML 🙏: MLOps framework to create reproducible pipelines.
darts - A python library for easy manipulation and forecasting of time series.
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
Keras - Deep Learning for humans