The e-commerce has taken the world with the storm and thrown new challenges to the brick & mortar industry. Due to high demand and supply, the eCommerce industry is growing by every passing moment. The e-Commerce industry is expecting to grow at 13-25% at a 5-6% growth rate through 2018.
Data is everything for the company and the clients as well. On an everyday basis, businesses need to take the extra step to secure and guard their data from any kind of breach. Companies are confronted with greater data protection compliance issues than ever before.
Incorporating smart data transformation technologies across processes allows firms to be flexible and responsive by combining human intelligence with AI, ML, and RPA. Raw data can be transformed into standardised, schema-compliant XML to aid in strategic decision-making.
Data annotation is the process of labelling data and meta data in order to train computer-vision-based algorithms. This information might take the shape of text, videos, photographs, social media material, and so on. Labelling, on the other hand, is done with tags, making it easier for AI-based classifiers to compute characteristics. Annotation in machine learning is developed to ensure the target of interest is observable or recognizable. Semantic segmentation, lines and splines, bounding boxes, 3D cuboid annotation, polygons, phrase chunking, text classification, entity linking, and many other approaches are examples of data annotation techniques.
