https://github.com/sefakcmn00/tensorflow_machine_learning_simple-

Artificial Neural Network(ANN) Perceptron
https://github.com/sefakcmn00/tensorflow_machine_learning_simple-

data mathplotlib pandas pandas-dataframe pandas-python sklearn tensorflow-examples tensorflow2

Last synced: 7 days ago
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Artificial Neural Network(ANN) Perceptron

• Host: GitHub
• URL: https://github.com/sefakcmn00/tensorflow_machine_learning_simple-
• Owner: sefakcmn00
• Created: 2022-08-09T14:42:46.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2022-08-09T14:45:16.000Z (over 2 years ago)
• Last Synced: 2024-11-10T07:10:15.490Z (about 2 months ago)
• Topics: data, mathplotlib, pandas, pandas-dataframe, pandas-python, sklearn, tensorflow-examples, tensorflow2
• Language: Jupyter Notebook
• Homepage:
• Size: 198 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Artificial Neural Network(ANN)

Perceptron --> ARTIFICIAL NEURON

Input1 --->

Input2 ------------ -> DATA ----> Output

Bias ----->

Sigmoid Function = takes a value between 0 and 1 and is generally useful for our classification problems

Tanh(Hyperbolic Tangent) = Takes values ​​between -1 and 1, and with negative values ​​it provides a wider scope and is often used in zeroing operations.

ReLU(Rectified Linear Unit) = 0 and your end It takes value among others and is frequently encountered in the field of deep learning. The given operation takes the value of =0 if not, the value of -1 if not.

Linear Functions f(x)= takes x and can take infinite values.

Regression = Is there a relationship between the height of the children and the height of the fathers? Children's heights tend to be close to the mean in the total data set. Y=a*x + b

z=ag +bf(z)=estimatedValue(estimate of neuron) Quadratic Cost=sum(actualValue - approximate value)**2/ Cross Entropy Cost=( -1/n)sum(actualValueIn(estimatedValue)(1-actualValue)ln(1-exactValue)

Gradient Descent = the optimization function we use to find the minimum of a function We can use it to minimize the Cost function.