Topic: Neural Networks

 Option I: You can conduct research on a topic related to Data Analytics, or Machine Learning. It is highly recommended that the topic is related to your research area of interest or on a recent/upcoming area of Data Analytics, Machine Learning or the umbrella field of Data Science in general. Your final deliverable will be formatted for submission to a conference.Paper according to template of CFP (Call for papers)/ Conference style.

• Papers should include the following sections: Introduction, (Literature Review), Methodology, Findings and Conclusion
• Papers length should be in the range of 5000- 6000 words (excluding references and appendices).
• Tables/figures/graphs should be inserted as close as possible to the location where they are cited. Headings should be centered for each figure/ graph and should be 12 font size, bold face and all caps.
• Equations should be placed on separate lines and numbered consecutively, with the equation numbers placed within parentheses and aligned against the left
• References should be in APA style

NEURAL NETWORKS 3

Neural Networks

Name: Group – 5

Institution: Cumberland University

Neural Networks

Machine learning refers to the application of artificial intelligence that leads to the provision of systems with the ability of improve and learn automatically without being programmed. It is a process that clearly focuses on the general development of the computer programs that have an access to data and can be clearly used for the learning process themselves (Priddy & Keller, (2015). The procedure involved in learning entails the use of observations such as direct experience or through the use of instruction. It is a practice that is deeply aligned to the use of computers to ensure that functions and operations take place in the required manner.

Neural networks is a topic in machine learning that is highly essential. It refers to a set of algorithms that are loosely modelled after the human brain. The algorithms are created to recognize respective patterns. Through them, the interpretation of sensory data through a machine perception. Clustering raw input and labelling is done (Burkov, 2019). The use of neural networks aids the classification and clustering which are key important topics that need to be appropriately addressed in this case. Thinking of them as the classification and clustering layer that is found on the top of the data applied in management and storage are key matters of concern.

The classifications of the tasks are dependent on the labeled datasets. This implies that humans need to ensure that they transfer their knowledge to the data for the neural network to learn the existing correlation that exists between the data and the labels (Burkov, 2019). The activity is defined as supervised learning which is a key practice that entails face detection, the recognition of gestures through the videos, the identification of the images and the classification of texts.

References

Burkov, A. (2019). The hundred-page machine learning book.

Priddy, K. L., & Keller, P. E. (2015). Artificial neural networks: An introduction. Bellingham, Wash: SPIE Press.