Episode 11: XGBoost special
AWS AI & Machine Learning Podcast
English - February 24, 2020 17:00 - 18 minutes - 13 MBTechnology Education How To cloud computing aws amazon web services machine learning deep learning artificial intelligence data science tensorflow pytorch Homepage Download Google Podcasts Overcast Castro Pocket Casts RSS feed
In this episode, I talk about XGBoost 1.0, a major milestone for this very popular algorithm. Then, I discuss the three options you have for running XGBoost on Amazon SageMaker: built-in algo, built-in framework, and bring your own container. Code included, of course!
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Additional resources mentioned in the podcast:
* XGBoost built-in algo: https://gitlab.com/juliensimon/ent321
* XGBoost built-in framework: https://gitlab.com/juliensimon/dlnotebooks/-/blob/master/sagemaker/09-XGBoost-script-mode.ipynb
* BYO with Scikit-learn: https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.ipynb
* Deploying XGBoost with mlflow: https://youtu.be/jpZSp9O8_ew
* New model format: https://xgboost.readthedocs.io/en/latest/tutorials/saving_model.html
* Converting pickled models: https://github.com/dmlc/xgboost/blob/master/doc/python/convert_090to100.py
This podcast is also available in video at https://youtu.be/w0F4z0dMdzI.
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