Deep Learning is a branch of ML (Machine Learning) concerned with algorithms inspired by the functions and structure of the key components of artificial neural networks.
DurationDeep Learning is a branch of ML (Machine Learning) concerned with algorithms inspired by the functions and structure of the key components of artificial neural networks. Deep learning is a set of entirely new technologies and algorithms to get this done in extraordinarily different ways.
At the very core of ML, complex and representative human tasks have already been shifted under the domain of ML. In this course, you will discover that the entire process is not a race between man and machine; instead, it is a new paradigm where time-consuming processes are done faster with the help of ML.
Here, you will also explore why and how Deep learning is considered the most scalable and performance-based algorithm for data analysis and processing. IT Professionals and Business analysts who are keen to learn and know about the implications of ML may consider joining this course.
Prerequisites
It is recommended that you are familiar with high-level programming language like Python.
It is expected that you are familiar with probability and linear algebra.
It will be considered as an added advantage if you have some experience of working with Deep Learning.
What will you gain after this course
Supervised, unsupervised and semi-supervised Algorithm are the critical building blocks of Deep Learning which is an excellent advantage for Deep Learning professionals
Reinforcement algorithm is an integral part of Deep Learning using which the system can fetch the status of the process through reinforcement signals
Deep Learning will help to predict the desired behavior of a newly developed process or model
Deep Learning is now being considered as the skill of the future technology
It is possible to develop better career growth with the help of Deep Learning
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The course provides an overview of the essentials of the TensorFlow and deep neural networks. The course equips delegates with the comprehensive knowledge of various types of the Deep Architectures such as Recurrent Networks and Convolutional Networks.
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