time-series-forecasting

Exploring different projects related to time-series prediction/forecasting

Creating environment and installing packages

Assuming you have python and pip installed

1. Install virtual environment -> pip3 install virtualenv
2. Create the virtual env -> virtualenv forecast / python3 -m virtualenv forecast
3. Activate the virutal env -> source forecast/bin/activate
4. Install all the packages -> pip3 install -r requirements.txt
5. Run jupyterlab -> jupyter lab

In some of the case, having conda environment is better

Assuming you have anaconda installed

1. Create conda environment -> conda create -n forecast python=3.8
2. Activate the conda env -> source/conda activate forecast
3. Install all the packages -> pip/pip3 install -r requirements.txt
4. Run jupyterlab -> jupyter lab

Types of sensor data

Live Data: I want to know when something is not working.
Historical Data: I want to keep logs of when something has and has not been working.
Analytical Data: I want to understand why something isn’t working.
Predictive Data: I want to know when something will stop working.
Data for Change: I want to change how something works.