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1. Keras: Keras is an open source high-level neural network library written in Python. It was originally written by François Chollet in 2015 and developed by various developers. Keras is  capable of running on top of TensorFlow, Microsoft Cognitive Toolkit or Theano. Focused on being user-friendly, modular, and extensible. It was developed with a focus on enabling fast experimentation; It also allows users to productize deep models on smartphones (iOS and Android), on the web, or on the Java Virtual Machine. It offers a higher-level, a more intuitive set of abstractions that make it easy to develop deep learning models regardless of the computational backend use. Version updates:   https://github.com/keras-team/keras/releases Upcoming conference:   https://conferences.oreilly.com/artificial-intelligence 2.Python: Python is widely used as a general-purpose, high-level programming language. It was initially designed by Guido van Rossum in 1991 and developed by Python

Deep Learning (also known as deep structured learning or Hierarchical learning) is a subdivision of machine learning in Artificial Intelligence that has networks which are capable of learning data representations, as opposed to task-specific algorithms. Learning can be supervised, semi-supervised or unsupervised. It deals with algorithms inspired by the structure and function of the brain, allowing computers to solve a host of complex problems that couldn't otherwise be tackled. Deep Learning is being widely used in industries to solve large number of problems like. Image Recognition: Deep Neural Nets are used to identify objects in an image.  Voice Generation: Products like Amazon Alexa uses deep learning to generate voice and interact with humans. Self Driving Vehicles: Google’s self driving car is based on Machine Learning and Deep Learning algorithms. It can drive at a precision of 98% in dark, while its raining and in high terrain areas. Produci