Tariq Rashid - A Gentle Introduction to Neural Networks (with Python)
Make Your Own Neural Network - Tariq Rashid.pdf
This book provides comprehensive coverage of neural networks, their evolution, their structure, the problems they can solve, and their applications. It describes the use of neural networks in machine learning: deep learning, recurrent networks, and other supervised and unsupervised machine-learning algorithms. In this book, highly qualified multidisciplinary scientists grasp their recent researches motivated by the importance of Artificial Neural Networks ANN. It addresses advanced applications and innovative case studies for different fields using ANN. This book provides a clear and detailed coverage of fundamental neural network architectures and learning rules.
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Update : When I wrote this article a year ago, I did not expect it to be this popular. Since then, this article has been viewed more than , times, with more than 30, claps. Many of you have reached out to me, and I am deeply humbled by the impact of this article on your learning journey. This article also caught the eye of the editors at Packt Publishing. Shortly after this article was published, I was offered to be the sole author of the book Neural Network Projects with Python. Today, I am happy to share with you that my book has been published!
But what if machine learning wasn't so hard? What if you could build your own Neural Network from scratch, using basic Python? Neural Networks are machine learning algorithms loosely modeled on the human brain. They are great at solving complex problems like image recognition and speech processing. Even though Neural Networks can solve complex problems, their implementation is fairly easy, and only uses high school level maths and if even that scares you, I will cover all the maths required with examples. Soon, he grew disillusioned by fixing dangling pointers, memory leaks, race conditions, bugs which only appeared once every two weeks.