**McCulloch-Pitts Neuron **it is known as Mankinds first Algorithm for deep learning. It is based on normal mathematical functions/operations to train the program. It is basically based on neurons of Human brains.

**Dendrite**: Receives signals from other neurons

**Soma**: Processes the information

**Axon**: Transmits the output of this neuron

**Synapse**: Point of connection to other neurons

**McCulloch-Pitts Neuron**

It uses binary activation function which means the inputs should be only in 2 different numbers **0 **or **1 **and the algorithm will give results in the form of **0 **and **1** only.

- The firing state is binary
**(1= fire, 0=not fire).** - Weights in the network remain the same throughout the program.
- It was able to solve Linear separable problems.
- There is no bias. This algorithm is known as the unbiased deep learning algorithm.
- It was able to solve Logical Gates
**AND, OR, NOT.**

**AND GATE:**

`if(sum)>threshold:`

output=1

else:

output=0

**Steps to solve manually:**

- Assume weight = 0(discard because weight cannot be 0 if we multiply it with any given input it will result in 0 itself).
- Assume weight = 1.
- Using the formula we will calculate
**threshold value**using the input x1,x2 from the input of AND gate. `x1w+x2w= 1x1+0x1`

- From step 4 we can get the value
**2**which is value for the**threshold.**

**NAND GATE **

Let’s solve NAND Gate using the same steps above:

Let’s assume w=-1 so when x1=x2=0.

`yin=x1w1+x2w`

(0x-1 + 0x-1=0)

when

x1=1

`x1=1 =>1x-1+0x-1= -1`

x2=0

x1=0 `0x-1+1x-1=-1`

x2=1

x1=1`1x-1+1x-1=-2`

x2=1

**Result:**

** 0 1 1**

**-1 1 1**

**-1 1 1**

**-2 0 0**

**the algo:**

if yin>=-1 then y=1 else: y=0

**Your task is to solve OR, NOT Gate using the steps above.**