1926 Open source projects that are alternatives of or similar to Spark Notebook

When Apache Pulsar meets Apache Spark

Code for Agile Data Science 2.0, O'Reilly 2017, Second Edition

Apache Spark & Python (pySpark) tutorials for Big Data Analysis and Machine Learning as IPython / Jupyter notebooks

⛈️ Rumble 1.11.0 "Banyan Tree"🌳 for Apache Spark | Run queries on your large-scale, messy JSON-like data (JSON, text, CSV, Parquet, ROOT, AVRO, SVM...) | No install required (just a jar to download) | Declarative Machine Learning and more

A stand alone, light-weight web server for building, sharing graphs created in ipython. Build for data science, data analysis guys. Aiming at building an interactive visualization, collaborated dashboard, and real-time streaming graph.

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 300 universities from 55 countries including Stanford, MIT, Harvard, and Cambridge.

A jupyter notebook that provides analysis for StarCraft 2 replays

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Python notebooks with ML and deep learning examples with Azure Machine Learning Python SDK | Microsoft

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

Example project implementing best practices for PySpark ETL jobs and applications.

Python Helper library for Jupyter Notebooks

Completed assignments and coding challenges from the Lambda School Data Science program.

A simple Spark-powered ETL framework that just works 🍺

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Content for architecting a data science platform for products using Luigi, Spark & Flask.

📚 Notebook storage and publishing workflows for the masses

📖 每一个伟大的思想和行动都有一个微不足道的开始

A pure Python implementation of Apache Spark's RDD and DStream interfaces.

The data journalism platform with built in training

Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.

简单的可视化湖州通话数据 假设数据量很大，没法用浏览器直接绘制热力图，把绘制热力图这一步骤放到线下计算分析。使用Apache Spark并行计算数据之后，再使用Apache Spark绘制热力图，然后用leafletjs加载OpenStreetMap图层和热力图图层，以达到良好的交互效果。现在使用Apache Spark实现绘制，可能是Apache Spark不擅长这方面的计算或者是我没有设计好算法，并行计算的速度比不上单机计算。Apache Spark绘制热力图和计算代码在这 https://github.com/yuanzhaokang/ParallelizeHeatmap.git .

Distributed Deep Learning, with a focus on distributed training, using Keras and Apache Spark.

Ways of doing Data Science Engineering and Machine Learning in R and Python

📘 The interactive computing suite for you! ✨

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.

🚚 Agile Data Preparation Workflows made easy with dask, cudf, dask_cudf and pyspark

Efficient variant-call data storage and retrieval library using the TileDB storage library.

📝 Web-based, reactive Datalog notebooks for data analysis and visualization

Spark structured streaming examples with using of version 3.0.0

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Word2Vec models with Twitter data using Spark. Blog:

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R on Apache Spark (SparkR) tutorials for Big Data analysis and Machine Learning as IPython / Jupyter notebooks

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Collection of open-source Spark tools & frameworks that have made the data engineering and data science teams at Swoop highly productive

Một cuốn sách tương tác về học sâu có mã nguồn, toán và thảo luận. Đề cập đến nhiều framework phổ biến (TensorFlow, Pytorch & MXNet) và được sử dụng tại 175 trường Đại học.

A Clojure dataframe library that runs on Spark

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

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Scalable Data Science, course sets in big data Using Apache Spark over databricks and their mathematical, statistical and computational foundations using SageMath.

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A Jupyter notebook using some standard techniques for data science and data engineering to analyze data for the 2017 flooding in Houston, TX.

The Archives Unleashed Toolkit is an open-source toolkit for analyzing web archives.

🎈 Simple reactive notebooks for Julia

Data Accelerator for Apache Spark simplifies onboarding to Streaming of Big Data. It offers a rich, easy to use experience to help with creation, editing and management of Spark jobs on Azure HDInsights or Databricks while enabling the full power of the Spark engine.

Educational notebooks on quantitative finance, algorithmic trading, financial modelling and investment strategy

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A PureScript, browser-based implementation of LDA topic modeling.

A guide on how to set up Jupyter with Pyspark painlessly on AWS EC2 clusters, with S3 I/O support

Machine Learning Platform for Kubernetes (MLOps tools for experimentation and automation)