5 ms·

Anyone know of any practical ways to get started with this?

octonion137 3y ago
https://xgboost.readthedocs.io/en/stable/get_started.html https://xgboost.readthedocs.io/en/stable/get_started.html
felixleungsc 3y ago
Maybe check out this recap on the M5 competition? It has links to notebooks and some of the top solutions. https://www.kaggle.com/competitions/m5-forecasting-accuracy/discussion/163414 https://www.kaggle.com/competitions/m5-forecasting-accuracy/...
hackerlight 3y ago
Kaggle.com. Sign up to a competition or download a dataset. Install python 3.11, and the libraries sklearn, lightgbm, pandas, matplotlib and numpy Ask a LLM to write a python script that loads the data and fits a model to the data and summarizes/plots some results. Jupyter Lab with autoreload, and using a python virtual environment are recommended.
schattschneider 3y ago
Here is a short intro on the theory of Gradient Boosted Decision Trees: https://developers.google.com/machine-learning/decision-forests/intro-to-gbdt https://developers.google.com/machine-learning/decision-fore... And here is a practical intro to it, you can run it right in your browser if you open it in Colab: https://www.tensorflow.org/decision_forests/tutorials/beginner_colab https://www.tensorflow.org/decision_forests/tutorials/beginn...
abhgh 3y ago
If you're talking about Gradient Boosting, I've a somewhat popular answer on Quora from ages ago [1]. [1] https://qr.ae/pKJPbm https://qr.ae/pKJPbm
iambateman 3y ago
i'm using this tutorial to get started: https://www.youtube.com/watch?v=Wqmtf9SA_kk https://www.youtube.com/watch?v=Wqmtf9SA_kk
mnky9800n 3y ago
I used to be an xgboost bro but these days I'm schilling for catboost. Anyways both have lots of examples online. The truth is without a problem interesting to you there's not much reason to learn about them unless you simply find gradient boosting algorithm elegant. Otherwise I would take some intro to machine learning course.
- bdjsiqoocwk 3y ago
  > used to be an xgboost bro You sound like a moron.
  - mnky9800n 3y ago
    Thanks internet stranger.
ianspektor 3y ago
(temporian developer here) Here's a simplified version of the approach (i.e. performing strong feature engineering, then converting the multivariate time series data to a panel/tabular dataset and training a boosting trees model on it), using temporian (a much improved alternative to pandas for working with temporal data) and xgboost: https://temporian.readthedocs.io/en/stable/tutorials/m5_competition/ https://temporian.readthedocs.io/en/stable/tutorials/m5_comp...

https://xgboost.readthedocs.io/en/stable/get_started.html https://xgboost.readthedocs.io/en/stable/get_started.html

Maybe check out this recap on the M5 competition? It has links to notebooks and some of the top solutions. https://www.kaggle.com/competitions/m5-forecasting-accuracy/discussion/163414 https://www.kaggle.com/competitions/m5-forecasting-accuracy/...

hackerlight 3y ago

Kaggle.com. Sign up to a competition or download a dataset. Install python 3.11, and the libraries sklearn, lightgbm, pandas, matplotlib and numpy Ask a LLM to write a python script that loads the data and fits a model to the data and summarizes/plots some results. Jupyter Lab with autoreload, and using a python virtual environment are recommended.

schattschneider 3y ago

Here is a short intro on the theory of Gradient Boosted Decision Trees: https://developers.google.com/machine-learning/decision-forests/intro-to-gbdt https://developers.google.com/machine-learning/decision-fore... And here is a practical intro to it, you can run it right in your browser if you open it in Colab: https://www.tensorflow.org/decision_forests/tutorials/beginner_colab https://www.tensorflow.org/decision_forests/tutorials/beginn...

abhgh 3y ago

If you're talking about Gradient Boosting, I've a somewhat popular answer on Quora from ages ago [1]. [1] https://qr.ae/pKJPbm https://qr.ae/pKJPbm

iambateman 3y ago

i'm using this tutorial to get started: https://www.youtube.com/watch?v=Wqmtf9SA_kk https://www.youtube.com/watch?v=Wqmtf9SA_kk

mnky9800n 3y ago

I used to be an xgboost bro but these days I'm schilling for catboost. Anyways both have lots of examples online. The truth is without a problem interesting to you there's not much reason to learn about them unless you simply find gradient boosting algorithm elegant. Otherwise I would take some intro to machine learning course.

bdjsiqoocwk 3y ago
> used to be an xgboost bro You sound like a moron.
- mnky9800n 3y ago
  Thanks internet stranger.

ianspektor 3y ago

(temporian developer here) Here's a simplified version of the approach (i.e. performing strong feature engineering, then converting the multivariate time series data to a panel/tabular dataset and training a boosting trees model on it), using temporian (a much improved alternative to pandas for working with temporal data) and xgboost: https://temporian.readthedocs.io/en/stable/tutorials/m5_competition/ https://temporian.readthedocs.io/en/stable/tutorials/m5_comp...