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donnemartin / data-science-ipython-notebooks

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Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

python aws data-science machine-learning caffe theano big-data spark deep-learning hadoop tensorflow numpy scikit-learn keras pandas kaggle scipy matplotlib mapreduce
  • Updated Oct 1, 2020
  • Python
cube.js

cube-js / cube.js

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flink-learning

zhisheng17 / flink-learning

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flink learning blog. http://www.flink-learning.com 含 Flink 入门、概念、原理、实战、性能调优、源码解析等内容。涉及 Flink Connector、Metrics、Library、DataStream API、Table API & SQL 等内容的学习案例，还有 Flink 落地应用的大型项目案例（PVUV、日志存储、百亿数据实时去重、监控告警）分享。欢迎大家支持我的专栏《大数据实时计算引擎 Flink 实战与性能优化》

mysql redis elasticsearch streaming kafka spark influxdb rabbitmq clickhouse hbase stream-processing opentsdb loki flink rocketmq
  • Updated Aug 11, 2020
  • Java

donnemartin / dev-setup

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macOS development environment setup: Easy-to-understand instructions with automated setup scripts for developer tools like Vim, Sublime Text, Bash, iTerm, Python data analysis, Spark, Hadoop MapReduce, AWS, Heroku, JavaScript web development, Android development, common data stores, and dev-based OS X defaults.

nodejs mysql python git vim macos linux bash redis cli mac aws elasticsearch cloud spark mongodb iterm2 sublime-text postgresql android-development
  • Updated Jun 20, 2020
  • Python

h2oai / h2o-3

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Open Source Fast Scalable Machine Learning Platform For Smarter Applications: Deep Learning, Gradient Boosting & XGBoost, Random Forest, Generalized Linear Modeling (Logistic Regression, Elastic Net), K-Means, PCA, Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

python java data-science machine-learning multi-threading opensource r big-data spark deep-learning hadoop random-forest gpu naive-bayes h2o distributed pca gbm ensemble-learning automl
  • Updated Oct 10, 2020
  • Jupyter Notebook
mmlspark

Azure / mmlspark

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[LightGBM] Regression: how to penalize negative predictions

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brunocous
brunocous commented Sep 2, 2020

I have a simple regression task (using a LightGBMRegressor) where I want to penalize negative predictions more than positive ones. Is there a way to achieve this with the default regression LightGBM objectives (see https://lightgbm.readthedocs.io/en/latest/Parameters.html)? If not, is it somehow possible to define (many example for default LightGBM model) and pass a custom regression objective?

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salesforce / TransmogrifAI

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