‫Let's start with perceptions.
‫Like in biology.
‫A single cell of our nervous system is called a neuron in artificial neural networks.
‫One of the earliest such artificial neuron was a perception perception was the lab in 1950s.
‫Yes the work on neural networks began nearly 70 years ago.
‫Today we use other models of artificial neurons such as sigmoid neurons but to understand take my neurons
‫we need to first look at perception.
‫Here's a simple pictorial representation of how perception works.
‫Perception is this circle or a black box which takes in several binary inputs x1 x2 x3 and so on.
‫DL exam and produces a single binary output represented by byte by binary input and binary output.
‫I mean that these variables can only take two values for example zero and one true or false etc..
‫There are several ways in which these x1 x2 x3 can give us the desired output by one of the rule is
‫that we will multiply each of these input values with weight W1 W2 W3 and then compare if the final
‫value of the sum of these products is greater than a threshold value or not.
‫If the sum value is greater than the Perseid drone gives an output value of 1.
‫And if it is less than say sure it gives out an output value of 0.
‫Mathematically this is how we represent this logic.
‫This is the summation of weight with feature values.
‫Basically this means X1 input w 1 plus X2 into W2 plus x3 into W3 and so on the exam into W M the sum
‫of all these products is this left random.
‫We compared this sum the threshold value.
‫If this is less than the threshold we give an output of zero.
‫If it is more than the threshold we give output of 1
‫Let's take a simple example which may not be very realistic but you will get the idea of how this perception
‫functions.
‫Let's say you want to decide whether you should parties is a particular shirt or not.
‫You might make your decision by weighing up three factors whether this shirt is blue or not whether
‫the shirt is falsely or half sleeved and whether the fabric is cotton or not we can represent these
‫three variables using three binary variables.
‫For instance X1 is equal to one.
‫If the shirt is blue and it is 0.
‫If it is not blue x2 is equal to 1.
‫If it is fully believed and 0 if it is half sleeve and extra is equal to 1 for cotton fabric and 0 for
‫non cotton fabric.
‫Now suppose that you absolutely adored blue collared shirt and you would prefer food sleeved cotton
‫fabric shirt much Cleveland and fabric is not as important as the color of the shirt.
‫So here are a sample rate of importance that you assign to these features.
‫You give weight of 7 to the shirt color.
‫I have replaced the value of w 1 with this number 7.
‫We assign a weight of 4 to Cleveland and a weight of 2 to the fabric.
‫Finally we also take a threshold value of 8 to decide whether two parties pressured or not.
‫With these choices of weights and threshold.
‫Let's see which of these three showed would we buy.
‫So far this first shirt we have blue in the first column which signifies the color of the shirt.
‫It is half sleeved so half and the second column it is non garden so non Gordon.
‫The third column which is what fabric the fourth column is for calculation of some.
‫As I told you previously we calculate the product of weights the features.
‫Add them together to find we calculated some in the Fifth Column.
‫We have written the threshold value that is pre decided in the sixth column.
‫We compare this some value with detail shown value.
‫If the sum is greater than threshold we will buy a t shirt.
‫If the sum is less than threshold we will not buy a t shirt.
‫So let let's see what happens with this.
‫Shirt.
‫The fresh shirt is blue in color but blue.
‫We have X1 value of 1 for not blue.
‫It would have been 0 so X1 is 1 x2.
‫We just leave is zero because it is half sleep.
‫Fabric is non cotton which is again zero.
‫We find out the same product.
‫7 It is rated for color multiplied by the value of X 1 which is one plus 4 wear where for sleeves multiplied
‫by the value of x2 which is zero because it is half sleep plus 2 which is weighted for fabric multiplied
‫by the value of fabric which is zero because it is not cotton.
‫The final time we get is 7.
‫We compare this some value with the threshold value which is 8.
‫The sum is less than 8.
‫So we are not going to buy this shirt.
‫Let us do this activity for the second shirt.
‫The second shirt is blue colored full sleeved non Gordon fabric.
‫If you repeat the calculation the only difference is going to be the value of x2 for the full sleeve
‫shirt.
‫Extra will be 1 so 7 plus 4 is going to come out as eleven eleven is more than eight.
‫So we are going to buy this shirt.
‫Similarly for the third shirt which is not blue full sleeved cotton shirt.
‫Some comes out to be 6 which is less than 8 which means that we are not going to buy this shirt.
‫Can you now see how perception is deciding the output that whether you will buy a shirt or not.
‫It is just multiplying the values of the feature with corresponding weight and checking some against
‫the threshold value if the sum is larger than the threshold.
‫It gives one output if it is smaller then it gives other output.
‫This is a very simple example which I have given to make you understand how a perception is working.
‫In reality we solve much more complex problems in which we have numerous input variables and many conditions.
‫We will get to them in the due course of the lectures.
‫As you can see a perception requires these weights and this threshold value to give out an output.
‫And how will perception get the values of these parameters.
‫One ways we give the values in which case it is not learning.
‫It is simple programming.
‫The other ways learning when we provide deeper separation with historical data of which shots were selected
‫and which shirts were rejected and the perception decides debate and traditional value according to
‫that previous data.
‫By the way you can get different models by changing weights and to be sure.
‫For example if you want to select a shirt which is blue food sleeved and cotton only and no other combination.
‫This set of weight and threshold ensures that right out you will see only blue cotton full sleeve shirt
‫will be selected and no other shirt will pass through.
‫So that's about it.
‫This is a basic introduction to the perception we will extend this idea of perception in the next lecture.