TimeSynth
pycaret
| TimeSynth | pycaret | |
|---|---|---|
| 1 | 5 | |
| 326 | 8,428 | |
| 0.6% | 1.0% | |
| 0.0 | 9.4 | |
| 6 months ago | 4 days ago | |
| Jupyter Notebook | Jupyter Notebook | |
| MIT License | MIT License |
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TimeSynth
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What is the best way to generate synthetic OHLC data?
I have the same question so I cant give a direct answer. However, I've been thinking of using SDV and TimeSynth python packages to produce synthetic data for backtesting.
pycaret
- pycaret: An open-source, low-code machine learning library in Python
- Predictive Maintenance and Anomaly Detection Resources
- Pycaret
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How to look for help on data science?
Take a look at Pycaret python library. https://github.com/pycaret/pycaret
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What is your DS stack? (and roast mine :) )
If you want to try pycaret exists, not sure how similar it is to caret, but it does all the steps in ML project. And Gluon for DL.
What are some alternatives?
tsfresh - Automatic extraction of relevant features from 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.
SDV - Synthetic data generation for tabular data
pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)
ta - Technical Analysis Library using Pandas and Numpy
ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
tempo - API for manipulating time series on top of Apache Spark: lagged time values, rolling statistics (mean, avg, sum, count, etc), AS OF joins, downsampling, and interpolation
ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.
stingray - Anything can happen in the next half hour (including spectral timing made easy)!
imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
tsai - Time series Timeseries Deep Learning Machine Learning Pytorch fastai | State-of-the-art Deep Learning library for Time Series and Sequences in Pytorch / fastai
Twitter-sentiment-analysis - A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.