Deep learning with perceptron using tensor flow library

Deep learning with perceptron using tensor flow library
Author(s):
Chaitanya R, Amitkumar Marab, Varsha Patil, Zeba mariam
Keywords:
Deep Learning, Machine Learning, Perceptron Learning algorithm, TensorFlow
Abstract
In recent years, Deep Learning, Machine Learning, and Artificial Intelligence are highly focused concepts of data science. Deep learning has achieved success in the field of Computer Vision, Speech and Audio Processing, and Natural Language Processing. It has the strong learning ability that can improve utilization of datasets for the feature extraction compared to traditional Machine Learning Algorithm. Perceptron is the essential building block for creating a deep Neural Network. The perceptron model is the more general computational model. It analyzes the unsupervised data, making it a valuable tool for data analytics. A key task of this paper is to develop and analyze learning algorithm. It begins with deep learning with perceptron and how to apply it using TensorFlow to solve various issues. The main part of this paper is to make perceptron learning algorithm well behaved with non-separable training datasets. This type of algorithm is suitable for Machine Learning, Deep Learning, Pattern Recognition, and Connectionist Expert System.
Article Details
Unique Paper ID: 149620 Publication Volume & Issue: Volume 7, Issue 1 Page(s): 123 - 126
Article Preview & Download

Share This Article

NCSST-2021

AICTE Sponsored National Conference on Smart Systems and Technologies

Last Date: 25th November 2021

LATEST INNOVATION’S AND FUTURE TRENDS IN MANAGEMENT

Last Date: 7th November 2021