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Options for configuration of python libraries - Stack Overflow
2 projects | /r/learnpython | 14 May 2023
In search for a tool that needs comparable configuration I looked into mlflow and found this. https://github.com/mlflow/mlflow/blob/master/mlflow/environment_variables.py There they define a class _EnvironmentVariable and create many objects out of it, for any variable they need. The get method of this class is in principle a decorated os.getenv. Maybe that is something I can take as orientation.
[D] Is there a tool to keep track of my ML experiments?
2 projects | /r/MachineLearning | 13 May 2023
I have been using DVC and MLflow since then DVC had only data tracking and MLflow only model tracking. I can say both are awesome now and maybe the only factor I would like to mention is that IMO, MLflow is a bit harder to learn while DVC is just a git practically.
Looking for recommendations to monitor / detect data drifts over time
3 projects | /r/datascience | 15 Apr 2023
Dumb question, how does this lib compare to other libs like MLFlow, https://mlflow.org/?
Integrating Hugging Face Transformers & DagsHub
2 projects | /r/mlops | 27 Mar 2023
While Transformers already includes integration with MLflow, users still have to provide their own MLflow server, either locally or on a Cloud provider. And that can be a bit of a pain.
Any MLOps platform you use?
5 projects | /r/selfhosted | 25 Feb 2023
I have an old labmate who uses a similar setup with MLFlow and can endorse it.3 projects | /r/learnmachinelearning | 25 Feb 2023
MLflow - an open-source platform for managing your ML lifecycle. What’s great is that they also support popular Python libraries like TensorFlow, PyTorch, scikit-learn, and R.
Selfhosted chatGPT with local contente
3 projects | /r/selfhosted | 24 Feb 2023
even for people who don't have an ML background there's now a lot of very fully-featured model deployment environments that allow self-hosting (kubeflow has a good self-hosting option, as do mlflow and metaflow), handle most of the complicated stuff involved in just deploying an individual model, and work pretty well off the shelf.
ML experiment tracking with DagsHub, MLFlow, and DVC
4 projects | dev.to | 12 Jan 2023
Here, we’ll implement the experimentation workflow using DagsHub, Google Colab, MLflow, and data version control (DVC). We’ll focus on how to do this without diving deep into the technicalities of building or designing a workbench from scratch. Going that route might increase the complexity involved, especially if you are in the early stages of understanding ML workflows, just working on a small project, or trying to implement a proof of concept.
AI in DevOps?
2 projects | /r/devops | 6 Dec 2022
AWS re:invent 2022 wish list
2 projects | dev.to | 23 Nov 2022
I am seeing growing demand for MLflow (https://mlflow.org/) and I am seeing a lot of people looking at Databricks as commercial offering for MLflow. Alternatively, some popele are implementing something like Managing your Machine Learning lifecycle with MLflow. Therefore, I think this was on my wish list last year, but I really hope AWS announce a Managed MLFlow Service. I know version 2.X is too new but at least 1.X would be great start.
Complete: D214 - MSDA Capstone
4 projects | /r/WGU_MSDA | 15 Mar 2023
My rescue came from discovering some of the alternatives to ARIMA/SARIMA, which was the extent of what we had covered for time series data. A series of searches eventually led me to some automated time series analysis packages, one of which was Prophet, an open source time series package released by Facebook's core data science team. This was a life saver, being a much more efficient and more effective forecasting tool than sloooowly iterating through ARIMA/SARIMA models that seemed to want to fight with me. If you're going to do a time series analysis for your capstone, I strongly suggest taking a look at using Prophet.
Dec 12, 2022 FLiP Stack Weekly
20 projects | dev.to | 11 Dec 2022
Ask HN: Data Scientists, what libraries do you use for timeseries forecasting?
7 projects | news.ycombinator.com | 3 Nov 2022
[D] Time Series Question
2 projects | /r/MachineLearning | 25 Sep 2022
LSTM/CNN architectures for time series forecasting[Discussion]
3 projects | /r/MachineLearning | 6 May 2022
16 projects | news.ycombinator.com | 12 Apr 2022
Predição de ações na bolsa de valores com Python e Facebook Prophet
5 projects | dev.to | 23 Mar 2022
Prophet: Automação preditiva.
Time series analysis of Bitcoin price in Python with fbprophet ?!
2 projects | dev.to | 22 Dec 2021
Data Science toolset summary from 2021
13 projects | dev.to | 13 Nov 2021
Prophet - It is a time-series forecasting library built by Facebook. Prophet is a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well. Link - https://github.com/facebook/prophet
Personal Support at Internet Scale
6 projects | dev.to | 14 Oct 2021
We run an anomaly detection app powered by Facebook's Prophet forecasting library. It tells us if metrics dip or rise in unexpected ways ("Did signups drop? Is something broken with that flow?"). We built the service because customers kept reaching out to tell us some feature broke before we noticed. Normally these issues show up in product data, so the app looks for these anomalies and tells us when they happen.
What are some alternatives?
clearml - ClearML - Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
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.
darts - A python library for user-friendly forecasting and anomaly detection on time series.
zenml - ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.
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
greykite - A flexible, intuitive and fast forecasting library
guildai - Experiment tracking, ML developer tools
dvc - 🦉 Data Version Control | Git for Data & Models | ML Experiments Management
neptune-client - :ledger: Experiment tracking tool and model registry