K Chidananda (47 results)

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Taschenbuch. Condition: Neu. Neuware - Deep Learning is a subset collection of Machine Learning concerned where neural network algorithms inspired by human brain learn from large amount of data through several layers for nonlinear transformation, Deep learning domain techniques allows to extract features automatically from the Industrial fault detection dataset. Since it has the strong learning ability that can improve the utilization of the dataset for the feature extraction. It determines Industrial Processes fault in the input data by simulating the way the human brain detects the fault in the industrial processes.…

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Taschenbuch. Condition: Neu. Neuware -Deep Learning is a subset collection of Machine Learning concerned where neural network algorithms inspired by human brain learn from large amount of data through several layers for nonlinear transformation, Deep learning domain techniques allows to extract features automatically from the Industrial fault detection dataset. Since it has the strong learning ability that can improve the utilization of the dataset for the feature extraction. It determines Industrial Processes fault in the input data by simulating the way the human brain detects the fault in the industrial processes. 64 pp. Englisch.…

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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - An extreme learning machine (ELM) is a feed-forward neural network (FFN). It is playing a crucial role in image classification and it is a simple method for features learning and ELM is frequently used in sequential learning, batch learning, and incremental learning because of these leanings ELM is learning faster, speed, good generalization ability, ease of implementation and efficiency in classifications. In this work, we propose two stages: the feature mapping stage, feature learning stage in an extreme learning machine.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Speech Recognition using Convolution neural network, is used to recognized the words and digitize them and analyze the sound. It trains a deep learning model that detects the presence of speech commands in audio. It uses a convolution neural network to train a model. The model was trained for commands and background noise. The trained model getting accuracy of 96.34% while testing the data. Define the level for audio processing and the level of identification in Hz and build an audio interface viewer that can interpret audio from your micro phone. When we speak commands it detects and visualize it and we speak other than commands it shows unknown. When we not speaking anything it detecting background noise.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Big data analytics is a form of advanced analytics, which involve complex applications with elements such as predictive models, statistical algorithms and what-if analysis powered by analytics systems. Organizations can use big data analytics systems and software to make data driven decisions that can improve business-related outcomes. The benefits may include more effective marketing, new revenue opportunities, customer personalization and improved operational efficiency. With an effective strategy, these benefits can provide competitive advantages over rivals. Data analysts, data scientists, predictive modelers, statisticians and other analytics professionals collect, process, clean and analyze growing volumes of structured transaction data as well as other forms of data not used by conventional BI and analytics programs. In this book, the topics discussed are about basics of big data analytics, Hadoop ecosystem Components, how to write a MapReduce Program, Hadoop Writables along with some of the big data processing tools such as pig and hive. …