LGBM
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What is LGBM?
Light Gradient Boosting Machine (LightGBM) is a gradient boosting framework developed by Microsoft. It is known for its efficiency and effectiveness in handling large datasets with high dimensionality. LightGBM uses tree-based learning algorithms and supports parallel and GPU learning. It is commonly used for classification, regression, and ranking tasks, especially where speed and memory usage are critical.
What other technologies are related to LGBM?
LGBM Competitor Technologies
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LGBM Complementary Technologies
scikit-learn
Scikit-learn provides tools for model selection, preprocessing, and evaluation that can be used in conjunction with LGBM. It also provides simpler models to benchmark LGBM against.
Pandas
Pandas is used for data manipulation and analysis, providing data structures like DataFrames that are commonly used as input for LGBM.
Spark
Spark can be used for distributed data processing and feature engineering at scale, providing data that can be used to train LGBM models on large datasets.
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Which job functions commonly mention LGBM?
MLOps Engineer
0.3% of all MLOps Engineer jobs mention LGBM
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jobs on Sumble
Mining Engineer
0.1% of all Mining Engineer jobs mention LGBM
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jobs on Sumble
Data Scientist
0.1% of all Data Scientist jobs mention LGBM
View 138
jobs on Sumble
Machine Learning
44 Machine Learning jobs mention LGBM
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jobs on Sumble
Actuary
6 Actuary jobs mention LGBM
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jobs on Sumble
Which organizations are mentioning LGBM?
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