Two training algorithms for artificial neural network models.

A tutorial on Conjugate Gradient Descent and Newton's Method.Go through the PPT and see if you can understand the concept and apply the same.If not do reply me.

Comments

Post a Comment

Popular posts from this blog

Beginners Guide to Cuckoo Search Algorithm Part 2

Image
Founding and Honorary Editor Innovate for Sustainability Subscribe to this blog Publish your book with EIS Publishers Instructor of Self Paced Course on Six-week course on Introduction to Remote Sensing and GIS Sponsored by Ashwagandha and Other Products for Enhancing Immunity.. Nutrilite(Use 13238584 as ABO ID) Procure Hydrology Themed T-Shirts from Innovate S Returns from commissions donated to NGOs after deducting the cost of honorarium and maintenance.
Read more

Free Tutorial : AHB Part I

Image
The Hummingbirds Optimization Algorithm is a nature-inspired optimization algorithm that mimics the efficient and agile search strategy of hummingbirds in finding optimal solutions to complex problems. This algorithm has been widely adopted in fields such as engineering, computer science, and finance due to its ability to handle large-scale problems, adaptability to different problem domains, and robustness in finding near-optimal solutions. The algorithm's versatility and effectiveness have led to its successful implementation in solving diverse optimization problems across various industries. It has been used in engineering and design to optimize various systems and processes, such as structural design, control systems, and renewable energy. It has also been utilized in data mining and machine learning to enhance the efficiency of algorithms and improve predictive modeling. Future prospects for the algorithm include incorporating parallel computing techniques to enhance speed and...
Read more

Types of Neural Network

Types of Neural Networks :  There are two different types of neural network based on the learning mechanism - Supervised and Unsupervised Neural Networks where in case of the former a desired dataset is provided("teacher") with which the model predicted data is compared to find level of accuracy of the model.The Unsupervised neural network will try to identify the inherent properties(data mining) of the input dataset with the help of different unsupervised learning methods. Based on the signal transmission through the neural networks,neural network models can be divided into three distinct classes : Feed forward - where the signal is transmitted only in the forward direction(Input-Hidden-Output); Feedback - a feedback or error correction signal is transmitted back to the source so that deviation from the desired data is actuated and Recurrent - signal is transmitted both ways.Recurrent Neural Networks can use their internal memory to process a...
Read more