Industrial activities have been one of the primary source of Global Warming as the unregulated energy consumption in industries lead to emission of greenhouse gases in atmosphere. Though the problem may appear easy to solve, identifying right time, volume and area of savings have always been challenging in saving energy.

Data Visualization

OLAP data visualization libraries can be used to drill down, roll up or slice and dice the data from OLAP databases.

Data analysis

The data exploration helps in doing extensive analysis of different data types and in assisting to understand the patterns. Data visualisation helps in representing the insights graphically. Libraries in this section are used for analysis and visualisation of data.

Data Labeling

Libraries in this section are used for annotating data for creating training data for machine learning.

Data Manipulation

Listed libraries can be used for auto machine learning. AutoML will pick the best machine learning algorithm based on the dataset.

Kit Solution Source

https://github.com/kandikits/automl-starter

Kit Deployment Instructions

This sections has the instructions to install the kit. For the Auto ML kit source, the deployment instructions are: 1. Clone the automl-starter from the source: https://github.com/kandikits/automl-starter 2. Install the required libraries by 'pip install -r requirements.txt' 3. Navigate to the 'automl-classification-pycaret.ipynb' and open and run each cellsPlease add specific deployment instructions for this kit e.g. Installation, Dependencies etc.