Graphic design python turtle 🐢

By Kajal Vishwakarma -
from turtle import * import colorsys bgcolor('black') pensize(0) tracer(50) h=0 for i in range(300): c=colorsys.hsv_to_rgb(h,1,1) h+=0.9 color(c) forward(300) left(100) fd(i) goto(0,0) down() rt(90) begin_fill() circle(0) end_fill() rt(10) for j in range(5): rt(30) done() Please follow my blog and subscribe my channel for more videos and newly updates 👍👍👍👍👍 import turtle as t import colorsys t.bgcolor('black') t.tracer(100) h=0.4 def draw(ang,n): t.circle(5+n,60) t.left(ang) t.circle(5+n,60) for i in range(200): c=colorsys.hsv_to_rgb(h,1,1) h+=0.005 t.color(c) t.pensize(2) draw(90,i*2) draw(120,i*2.5) draw()
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Neural Network Architecture in machine learning

By Kajal Vishwakarma -

 Neural Network Architectures

An artificial neural network is a data processing system consists of a large number of highly interconnected processing elements (artificial neural) in an architecture inspired by the human brain. An artificial neural network (ANN) is represented using digraph. On the basis of learning machanism, there are several classes of neural network. In general, we may identify Three fundamentaly different classes of network architectures.

1. Single Layer Feedforward Network:- There are two layers input layer and output layer, in Single Layer Feedforward Network. The input layer neurons receive the input signals and the output layer neurons receive the output signals.

2. Multilayer Feedforward Network:- the Multilayer Feedforward Network comprises of multiple layers. Thus, this type of Architecture besides processing an input and output layer also contain one or more intermediary layer known as hidden layers.

3. Recurrent Network:- A recurrent network distinguishes itself from a feedforward neural network in that it has at least one feedback loop.




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