You have been hired by a startup specializing in the development of Artificial Intelligence solutions for various industrial sectors. Your role is to create a predictive model using sensor data from the plant to identify patterns that precede equipment failures. These failures can result in production interruptions, additional maintenance costs, and loss of operational efficiency. The goal is to create a predictive model that can identify potential failures in specific equipment based on values from other plant sensors, allowing the company to intervene proactively before problems occur.

The available data consists of sensor readings installed on the industrial equipment over time. These data may include variables such as temperature, pressure, vibration, electrical current, among other parameters relevant to the equipment's operation.

Your objective is to explore, analyze, and model sensor data to predict possible failures in industrial equipment. This involves data preparation, identification of patterns or anomalous behaviors that may indicate imminent failures, and the creation of a predictive model capable of accurately forecasting these failures.

• The code of the developed model, preferably in Python or the language of your choice, documented and organized.
• A concise presentation of the results obtained, highlighting the chosen metrics for model evaluation and key insights derived from the analysis.