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Description

Deep learning is an area of Machine Learning algorithms having multiple layers for feature extraction and transformation, each successive layer uses output from previous layer as an input. Deep learning includes learning of deep structured and unstructured representation of data and allow to build a solution optimized from algorithm to solve machine learning problems. It is fastest-growing field in machine learning using deep neural networks to abstract data such as images, sound and text. Thus deep learning has become growing trend in Machine learning to abstract better results when data is large and complex.

Research Infinite Solutions offers Deep Learning Training in India on the latest techniques for designing, training and deploying neural networks across a variety of application domains. We provide training to developers, data scientists and researchers looking to solve the world’s most challenging problems with Deep Learning.

Why Deep learning:

Advancement in Machine Learning, Artificial Intelligence and Deep Learning helps in many ways in our daily life. Machine helps in most logic and rule-based systems designed to solve problems by using a suite of algorithms to go through data to make and improve decision making process. But within Machine Learning, Deep Learning make sense of data using multiple layers of abstraction. As many companies across industries seek to use advanced computational techniques to find useful information hidden across huge data. Thus Deep Learning can create intelligent, self-learning machines which gave easiness to complex systems.

Benefits :

Works as a framework for Machine Learning which solves complex problems easily using techniques like convolutional neural network, recurrent neural network. Many tools make it beneficial, like natural language processing software tool which helps in computer decipher messages. Image recognition software tool enables the computer to search, sort and segment for object detection and speech recognition software tool allows human to interact with their smart gadgets. It provides simplicity, accuracy, flexibility with expert system.

Future Scope

In present Scenario, clients demand real time application, to process huge amount of data of business firms and blue chip stocks deep learning is used. Deep Learning is a key to learn from unstructured data beneficial in real-world applications whose networks can be successfully applied to big data for knowledge discovery, knowledge application and knowledge-based prediction. Helps researchers analyze medical data to treat diseases, doctors to analyze medical images thus improving patient’s care.

Research Infinite Solutions is a Data Science Company in India provides, Artificial Intelligent based platform which is able to deliver solutions for improvement and enhancement of various programs that uses Deep Learning networks to detect, predict and prevent advanced persistent threats in real time. AI has been focused on deep learning, which include training artificial neural networks on lots of data and then getting them to make inferences about new data. In classification of different diseases, support vector machine and machine learning is used,

Research Infinite Solutions is one of the leading Machine Learning company in India for providing Deep Learning Training in India. Our expertise handle project based on deep learning and AI able to design, train, deploy neural network and image processing using feature extraction. Further solve project over deep neural network model, fingerprint matching, image recognition, age estimation, word recognition, mapping, removal of high density noise using fuzzy filters. All of these is possible by a family of AI technique known as Deep Learning, though deep neural networks. Vision is to transform industry through deep learning technique with increasing percentage of accuracy. Performance in not just accuracy but to provide services.

Lecture 1 (Duration 2 hours)

History of Neural Networks, Introduction to Deep Learning Theory, Introduction to Deep Learning and Neural Networks.

Lecture 2 (Duration 2 hours)

NumPY/SciKit Learn basics.

Lecture 3 (Duration 2 hours)

Pandas

Lecture 4 (Duration 2 hours)

Introduction to Tensorflow and Theano.

Lecture 5 (Duration 2 hours)

Introduction to Keras, demonstration of Neural Network, building a basic Neural Network.

Lecture 6 (Duration 2 hours)

Neural network internals, activation functions, backpropagation, loss functions, weight inilialization.

Lecture 7 (Duration 2 hours)

Data normalization/Standardization, model tuning, deployment, and scaling, Deep Network topologies, feed Forward

Lecture 8 (Duration 2 hours)

Convolutional

Lecture 9 (Duration 2 hours)

Recurrent

Lecture 10 (Duration 2 hours)

How to Choose an Appropriate Neural Network

Lecture 11 (Duration 2 hours)

Tuning, overfitting, learning rate, adaptive learning rates, dropout, regularization

Lecture 12 (Duration 2 hours)

Advanced topics, import Keras into deeplearning4j for production, model Import,transfer learning, model serializer.