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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.

  • Updated Oct 1, 2020
  • Python

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.

  • Updated Oct 17, 2020
  • Jupyter Notebook
datapythonista
datapythonista commented Oct 13, 2020

We're working on having the backends in a more standardized and structured way. We are finishing moving backends to the backends/ directory, and moving shared code among backends to backends/base_*. The backends based on SQLAlchemy historically lived in ibis/sql. We moved them (MySQL move is still not merged at the time of writing this, see #2446), and after all backends are moved, would be

450+ AWS, Hadoop, Cloud, Kafka, Docker, Elasticsearch, RabbitMQ, Redis, HBase, Solr, Cassandra, ZooKeeper, HDFS, Yarn, Hive, Presto, Drill, Impala, Consul, Spark, Jenkins, Travis CI, Git, MySQL, Linux, DNS, Whois, SSL Certs, Yum Security Updates, Kubernetes, Cloudera etc...

  • Updated Oct 14, 2020
  • Python

50+ DockerHub public images for Docker & Kubernetes - Hadoop, Kafka, ZooKeeper, HBase, Cassandra, Solr, SolrCloud, Presto, Apache Drill, Nifi, Spark, Consul, Riak, and DevOps tools built various distros: Alpine, CentOS, Debian, Fedora, Ubuntu

  • Updated Oct 14, 2020
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