DOMAIN: Electronics and Telecommunication • CONTEXT: A communications equipment manufacturing company has a product which is responsible for emitting informative signals. Company wants to build a machine learning model which can help the company to predict the equipment’s signal quality using various parameters. • DATA DESCRIPTION: The data set contains information on various signal tests performed: 1. Parameters: Various measurable signal parameters. 2. Signal_Quality: Final signal strength or quality • PROJECT OBJECTIVE: The need is to build a regressor which can use these parameters to determine the signal strength or quality [as number]. Steps and tasks: [ Total Score: 10 points] 1. Import data. 2. Data analysis & visualisation • Perform relevant and detailed statistical analysis on the data. • Perform relevant and detailed uni, bi and multi variate analysis. Hint: Use your best analytical approach. Even you can mix match columns to create new columns which can be used for better analysis. Create your own features if required. Be highly experimental and analytical here to find relevant hidden patterns. 3. Design, train, tune and test a neural network regressor. Hint: Use best approach to refine and tune the data or the model. Be highly experimental here. 4. Pickle the model for future use.