| apache/spark |
37,661 |
|
2,394 |
939 |
about 2 years ago |
46 |
May 09, 2021 |
186 |
apache-2.0 |
Scala |
| Apache Spark - A unified analytics engine for large-scale data processing |
| donnemartin/data-science-ipython-notebooks |
25,668 |
|
0 |
0 |
over 2 years ago |
0 |
|
34 |
other |
Python |
| 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. |
| getredash/redash |
24,479 |
|
0 |
3 |
about 2 years ago |
2 |
May 05, 2020 |
595 |
bsd-2-clause |
Python |
| Make Your Company Data Driven. Connect to any data source, easily visualize, dashboard and share your data. |
| yeasy/docker_practice |
23,279 |
|
0 |
0 |
over 2 years ago |
9 |
December 01, 2021 |
6 |
|
Go |
| Learn and understand Docker&Container technologies, with real DevOps practice! |
| DataTalksClub/data-engineering-zoomcamp |
19,461 |
|
0 |
0 |
about 2 years ago |
0 |
|
27 |
|
Jupyter Notebook |
| Free Data Engineering course! |
| heibaiying/BigData-Notes |
14,872 |
|
0 |
0 |
over 2 years ago |
0 |
|
39 |
|
Java |
| 大数据入门指南 :star: |
| zhisheng17/flink-learning |
13,801 |
|
0 |
0 |
over 2 years ago |
0 |
|
8 |
apache-2.0 |
Java |
| flink learning blog. http://www.54tianzhisheng.cn/ 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》 |
| horovod/horovod |
13,755 |
|
20 |
16 |
about 2 years ago |
77 |
June 12, 2023 |
372 |
other |
Python |
| Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. |
| aalansehaiyang/technology-talk |
13,579 |
|
0 |
0 |
over 2 years ago |
0 |
|
6 |
|
|
| 【大厂面试专栏】一份Java程序员需要的技术指南，这里有面试题、系统架构、职场锦囊、主流中间件等，让你成为更牛的自己！ |
| deeplearning4j/deeplearning4j |
13,290 |
|
175 |
119 |
over 2 years ago |
54 |
August 10, 2022 |
624 |
apache-2.0 |
Java |
| Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation. |
