tensor-house
Prophet
tensor-house | Prophet | |
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4 | 221 | |
1,163 | 17,767 | |
- | 0.5% | |
7.5 | 6.2 | |
3 months ago | 1 day ago | |
Jupyter Notebook | Python | |
Apache License 2.0 | MIT License |
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tensor-house
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Supply Chain Uses Cases
I still have this on my reading list, it has quite some interesting SC applications. https://github.com/ikatsov/tensor-house
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How to use the code to do analysis with my data
Hi, how can i use the code of an analysis like this https://github.com/ikatsov/tensor-house/blob/master/pricing/price-optimization-multiple-time-intervals.ipynb but with my data?
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What are some applications of Data Science in Digital Marketing?
This is the companion github to the book, it doesn't have all the use cases, but there are a decent amount of code samples to get you started.
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Machine learning Applications in Marketing
Happy to help out! That website I linked has a link to the book PDF, so you can check it out yourself. I guess the Amazon reviews must have missed it, but there is a companion github for a selection of models in the book that may be helpful.
Prophet
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Moirai: A Time Series Foundation Model for Universal Forecasting
https://facebook.github.io/prophet/
"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."
- prophet: NEW Data - star count:17116.0
- prophet: NEW Data - star count:17082.0
- Facebook Prophet: library for generating forecasts from any time series data
- prophet: NEW Data - star count:16196.0
- prophet: NEW Data - star count:15889.0
What are some alternatives?
EconML - ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.
tensorflow - An Open Source Machine Learning Framework for Everyone
Robyn - Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.
darts - A python library for user-friendly forecasting and anomaly detection on time series.
models - A collection of pre-trained, state-of-the-art models in the ONNX format
scikit-learn - scikit-learn: machine learning in Python
Workshops - Workshops organized to introduce students to security, AI, blockchain, AR/VR, hardware and software
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
models - Models and examples built with TensorFlow
greykite - A flexible, intuitive and fast forecasting library
vectordb-recipes - High quality resources & applications for LLMs, multi-modal models and VectorDBs
MLflow - Open source platform for the machine learning lifecycle