The modern replacement for Jupyter Notebooks

General statistics, mathematical programming, and numerical/scientific computing scripts and notebooks in Python

Tellery lets you build metrics using SQL and bring them to your team. As easy as using a document. As powerful as a data modeling tool.

A notebook tutorial series for performing predictive maintenance using machine learning

Data analysis and reporting tool for quick access to custom charts and tables in Jupyter Notebooks and in the shell.

Discover fun stats about your Facebook Messenger usage such as: most used words, most active year, most active hours, etc. using this Jupyter Notebook

Pyhaystack is a module that allow python programs to connect to a haystack server project-haystack.org. Connection can be established with Niagara Platform running the nhaystack, Skyspark and Widesky. For this to work with Anaconda IPython Notebook in Windows, be sure to use "python setup.py install" using the Anaconda Command Prompt in Windows.…

Various notebooks we're working on from either our blog cfe.sh/blog or as general research.

A random set of notebooks to analyze the crypto markets

Query Kusto like a pro from the comfort of your Jupyter notebook

Automate your Jupyter notebooks and scripts as web-based reports, tools, widgets, dashboards, forms.

Introduction to MindSphere Analytics APIs - The notebooks use @mindconnect/mindconnect-nodejs CLI for API calls.

Analyze data any time, anywhere

The python notebook is on googles new collabatory tool. Its a churn model being run on 3 different algorithms to compare.

Project for the Big Data Computing course at the University of "La Sapienza" in Master in Computer Science A.A. 2021/2022

A repository of my activities, jupyter notebooks, datasets, projects, and resources used in machine learning algorithms for data science and deep learning

Build a movie recommendation data pipeline using Azure services for efficient data ingestion, transformation, and orchestration. Utilize Azure Blob Storage, Azure Databricks, and Azure Data Factory to implement collaborative filtering and PySpark ML for accurate movie recommendations.

This is the final project I had to do to finish my Big Data Expert Program in U-TAD in September 2017. It uses the following technologies: Apache Spark v2.2.0, Python v2.7.3, Jupyter Notebook (PySpark), HDFS, Hive, Cloudera Impala, Cloudera HUE and Tableau.

This repository contains codes developed in Python which deals with smart meter analytics. Building consumption dataset from Pecan Street Dataport was obtained along with temperature and irradiance data. The dataset was used to build machine learning models using linear regression, random forest deicision tree, Neural networks and Support vector…

Jupyter Notebook/Lab, web-based interactive development environment