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Machine-Learning Services

Machine-Learning Services

Machine learning can be the key to unlocking the value of corporate and customer data and enacting decisions that keep a company ahead of the competition. Currently, machine learning has been used in multiple fields and industries. It allows software applications to become accurate in predicting outcomes. For example, medical diagnosis, image processing, prediction, classification, learning association, regression, etc. Moreover, machine learning focuses on the development of computer programs.


Google says” Machine Learning is the future”, so the future of machine learning is going to be very bright and there will be 2.3 million jobs in the field of Artificial Intelligence and Machine Learning by 2022.

Products and Solutions

Brain Tumour Detection System

Brain Tumour Detection is a machine learning based system which makes the task of detecting the tumor easy, fast, and accurate. The main motivation for developing this model is in the present method of detecting the tumor the system is completely dependent on Human. Which may sometimes be a time-consuming process in some cases size of the tumor may be small which human eye may not be able detect. We have developed this system using convolution neural networks and image processing we have used Brain scan MRI images for training our system. We have obtained an accuracy of 97%.


The model is very user friendly and requires minimal knowledge of system. It can be operated on any Operating system with 64-bit configuration. The system will generate the result fast which helps in further process of medication the system is more advantages in the case of small size of the tumor in this case the medication can be provided in the early stage and can be cured in some cases. Using this the doctor can provide the services to a large set of patients. We can also build models which addresses other issues faced in the health sector which enables doctor to provide accurate and timely service.

Traffic Signs Recognizer

Traffic signs recognizer is machine learning based model which can be incorporated in the latest vehicles which recognizes the sings present on the road without depending on the human. The main motivation behind construction of this model is the driver may face issues such as the weather condition like heavy rain, fog, Low intensity of light, and the orientation and text on the sign board may mislead the driver. To address such issues, we have developed a convolution neural networks-based model which utilizes the concept of image processing for the task of recognition of traffic signs. It uses images taken by a camera from a moving vehicle.


In this model the images are captured by the front facing camara of the vehicle and these images are basically categorized as color based, shape based and learning based method. This system of recognition and classification of traffic signs would assist the highway engineers’ tasks of updating and maintaining them. This model provides driver safety and a fast accurate result. This doesn’t require any prior knowledge of the system. We have obtained an accuracy of 96%.