Neural Networks from Scratch in JAVA Completely using Object Orientated Approach

Опубликовано: 25 Апрель 2020
на канале: AMR.SMART.SYSTEMS

1,858

Vedio#1: Introduction and Neural Layer Class

• Not need to include complete libraries like NumPy, TensorFlow or Pytrouch
• Writing a lightweight and server independent application.
• More Experimentation.
Java V/s Python
• Code Reusability in Java Best as OOPs
• Java handles concurrency better than Python, Python is more sequential
• Speed – Using JVM for Just in Time compilation
• Platform independent - Write once run anywhere with JVM (Java Virtual machine)

Neural Layer Class
Neural Layer – Collection of a set of neurons.

Neurons – Multi Input , Single Out put ( i/p * Weights) =Activation Function
Activation Function – Bounding the values.
Error Correction – Back Propagation = Covered In next video

Video #2 - • Neural Networks from Scratch in JAVA ...
#Vedio2: Math Operations
Neural Network Math’s Operations Class
1) Activation functions – Sigmoid Function, Tanh Functions
2) Matrix Multiplication
3) Scalar Multiplication to matrix
4) Matrix Addition
5) Matrix Subtraction
6) Matrix Transpose
7) Matrix Normalization

Complete code of NNMath class-
http://86amruth.blogspot.com/2020/04/...