Machine learning algorithms have come a long way, and new computing technologies are supporting its evolution. The most challenging task while developing a machine learning based solution is data processing and choosing the customized algorithm. PredictSense, a machine learning automated platform, which is a part of such evolution, meets this challenge. It customizes the machine learning needs for businesses through its data transformation and model enhancement techniques.
Built on an open API structure, PredictSense uses high-end algorithms to address real-time complications in a short span of time. Since this product can be integrated into new or existing models, it finds its application in many segments such as banking, retail, and IoT, etc.
Operating PredictSense for business operations
PredictSense is easy to set up where a business can carry out user management, data upload & configuration, and model environment & testing. Let’s discuss each one in detail.
User Management: Upon successful integration, the user can begin by setting up a single/multiple projects (as per requirement) and scale it by creating sub-users.
Data upload and configuration: The data can be uploaded which is then processed and any issues, if occur, are resolved with PredictSense’s data analysis strategies. The data is configured using filters, test settings and data transformation strategies for higher efficiency and better results.
How PredictSense functions?
The core of PredictSense is responsible for its functionality. Here are the essential components of PredictSense:
- Data Transformation: Most of the data fed into the system is transformed by categorizing them. Since empty values and outliers exist too, they are handled using efficient strategies for data cleaning.
- Model Enhancement: All the hyper parameters are tuned to enhance the model as they can be used after the training.
- Model execution: The user can now select the most suited machine learning algorithm to develop a competitive model which can be easily deployed.
- Model Assessment: Lastly, the behaviour of the model is assessed using scoring parameters. The performance score and evaluation parameters give the model a rank on the leaderboard. The user can view the performance chart to visualize the competitive models.
Thus, PredictSense is a fine platform for automatic model generation and rapid model deployment thereby giving a customized machine learning solution. The visualization insights and accurate predictions make this product efficient. Most businesses prefer PredictSense as it generates quick responses and is easy to use.