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A Tiny Grammar of Graphics
4 projects | news.ycombinator.com | 14 Jun 2022
20+ Free Tools & Resources for Machine Learning
5 projects | dev.to | 31 Mar 2022
H2O.ai H2O is a deep learning tool built in Java. It supports most widely used machine learning algorithms and is a fast, scalable machine learning application interface used for deep learning, elastic net, logistic regression, and gradient boosting.
Data Science Competition
15 projects | dev.to | 25 Mar 2022
Complete: D214 - MSDA Capstone
4 projects | reddit.com/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 | reddit.com/r/MachineLearning | 25 Sep 2022
LSTM/CNN architectures for time series forecasting[Discussion]
3 projects | reddit.com/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?
tensorflow - An Open Source Machine Learning Framework for Everyone
darts - A python library for user-friendly forecasting and anomaly detection on time series.
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
MLflow - Open source platform for the machine learning lifecycle
sktime - A unified framework for machine learning with time series
Keras - Deep Learning for humans
pytorch-forecasting - Time series forecasting with PyTorch
pycaret - An open-source, low-code machine learning library in Python