Machine learning is that part of Artificial Intelligence (AI) system that allows systems to automatically learn and improve, without being programmed. The ML apps works of the available data and set of assumptions, and their ability to predict for a given situation varies. There are different types of assumptions, and their ability to predict for a given situation varies. There are different types of renforcement ML algorithms. Appropriate set woud be chosen for delivering the ML training.
Deep learning is an advanced aspect of ML. Deep learning is closer to human level learning. Deep learning is also capable of learning unsupervised from data that is unstructured or unlabeled. DL uses class of ML algorithms that uses multiple layers progressively extract higher-level features from raw data. Models are based on Artificial Neural Networks (ANN), eg. Convolutional Neural Networks (CNN)s, although they can also include propositional formulas or latent variables organized layer-wise in deep generative models, Boltzmann machines, for example.
Natural language processing (NLP) is the ability of an app to understand human language as it is used. NLP uses syntax and semantics to process. Syntax helps NLP to assess meaning from a language based on grammatical rules. Semantics involves the use and meaning behind words. NLP applies algorithms to understand the meaning and structure of sentences. Python provides a number of tool kits that helps in NLP application design.
Modern Artificial Intelligence (AI) when applied to image processing (IP) can help in the implementation of functionalities such as face recognition, detection and recognition of objects and actions in images and video, run visual search, etc. ForModFinServer, we propose just the static image processing part.Python provides a number of libraries that will help in image processing. Some of the important ones are SciKit, NumPy, SciPy etc. Suitable tool kit will be chosen for the training purposes.