Terms, buzzwords and definitions are carefully worded. — Computer vision algorithms analyze certain criteria in images and videos and apply learned interpretations to predictive or decision-making tasks. Image processing is not same as computer vision. It is about modifying or enhancing images, like optimizing brightness or contrast, increasing resolution, blurring sensitive information, or cropping. In image processing, we…

S3, EFS, EC2, SageMaker, DLAMI etc — With cloud deep learning, you can request as many GPU machines as needed, and scale up and down on demand. Amazon Web Services (AWS) provides an extensive ecosystem of services to support deep learning applications like SageMaker and Deep Learning Containers. Any deep learning project requires three essential resources —…

A model is an overfit when it has learned certain unique features of the training data, but not enough general ones to perform well on unseen data. It is thus not ready for real-world use. Causes: If a model has high variance and low bias, its training accuracy increases, but validation…

The term ‘big data’ implies an enormous amount and variety of structured and unstructured data that needs to be processed and updated at very high speeds. Data Warehouse A data warehouse facilitates the storage of structured and semi-structured data from various sources, both historical and current, that allows decision-makers to extract insights…

First, we make the data conducive to computers — that is, we convert it into vectors and matrices. The data also needs to be organized as samples and features. Then we split it into training, validation, and test sets. For the training set, for each sample, we have a target…