Prophet
tensorflow
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Prophet | tensorflow | |
---|---|---|
88 | 139 | |
14,431 | 164,981 | |
1.4% | 0.6% | |
6.5 | 10.0 | |
16 days ago | 2 days ago | |
Python | C++ | |
MIT License | Apache License 2.0 |
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.
Prophet
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Reverse Engineering Video Game Stock Prices
Prophet is a forecasting model made by Facebook.
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ARIMA models are solid though
I like FB Prophet and LinkedIn's GreyKite
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LSTM/CNN architectures for time series forecasting[Discussion]
Prophet
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Basic Time Series Prediction
I like Meta's Prophet. It's a flexible model that I feel is easy to understand and explain to non-technical stakeholders. Implementations for R and python. It can be as simple as a univariate series, or accept exogenous explanatory variables (categorical & continuous). Seasonality is part of the model, out of the box. It also has decent default parameters if you're not looking to do a lot of tuning. Lastly, the documentation is quite thorough and approachable. https://facebook.github.io/prophet/
- prophet: NEW Data - star count:14301.0
tensorflow
- TensorFlow 2.9.0
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How could I use batch normalization in TensorFlow?
I would like to use batch normalization in TensorFlow. I found the related C++ source code in core/ops/nn_ops.cc. However, I did not find it documented on tensorflow.org.
- [P] Neural Network for Image Classification
- When I'm on a project & cloning a repo, which branch should I clone?
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If data science uses a lot of computational power, then why is python the most used programming language?
For reference: In Tensorflow and JAX, for example, the tensor gets compiled to the intermediate XLA format (https://www.tensorflow.org/xla), then passed to the XLA complier (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla/service) or the new TFRT runtime (https://github.com/tensorflow/runtime/blob/master/documents/tfrt_host_runtime_design.md), or some more esoteric hardware (https://github.com/pytorch/glow).
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FFmpeg for Super Resolution on Ubuntu 20.04 : libtensorflow_framework Relink Error
Looks like it's tensorflow-related, however I have verified that tensorflow is working properly on my system. I could find nothing on Google, there's just one thread discussing exactly the same error (here), however there is still no solution as well. I am aware the error is not symlink related, but just in case this information is needed : (or see in gist)
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[Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org
I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource?
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TensorFlow saving into/loading a graph from a file
Save a model into a .pb file and load it back in using tf.train.write_graph() and tf.import_graph_def() (source)
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What's the purpose of tf.app.flags in TensorFlow?
And I found the implementation of this flags is in the tensorflow/tensorflow/python/platform/default/_flags.py
What are some alternatives?
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
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
darts - A python library for easy manipulation and forecasting of time series.
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
PyBrain
Keras - Deep Learning for humans
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.
MLflow - Open source platform for the machine learning lifecycle