DataScience_Community

Lets Understand Null Hypothesis and Alternate Hypothesis. Prerequisites : part 1:  What is Hypothesis Testing and When it is Used?   Null Hypothesis (H 0 ) : It is a well Established Fact or An Assumption which treats everything is similar and equal. Alternate Hypothesis(H a ) : The claim you want to prove. Note: H 0 and H a are always opposite to each other.                                                                                                                               https://keydifferences.com/ Example 1: Statement: During 18 th century, People used to believe that Sun revolves around the earth. Later Copernicus came and told that it is not true. ...

Hypothesis Testing  is an interesting topic for the interviewers to decide whether the interviewee is good at statistics. Unfortunately, This is the topic on where Most of us fumble upon. In this blog, I will try to explain what and why exactly the Hypothesis Testing is needed in layman way. Let’s get into it.   Whenever I listen the word Hypothesis Testing, The following quote comes into my mind.                        “INNOCENT UNTIL PROVEN GUILTY”   Let’s understand a practical scenario, what will happen in a court room if a person is guilty of a crime? 1. Firstly, The Judge always presumes that the person is Innocent. 2. Secondly, The Lawyer tries to prove that the person is guilty based on the Evidence.    Here, the lawyer is indirectly trying to reject the Judge’s presumption based on the collected evidence. This is what exactly happens in Hypothesis Testing. There will be a...

It is the basic algorithm at which everybody would like to start their learning in Data Science.             Now, what exactly the Linear Regression is 1.  Linear Regression is the supervised learning algorithm where it’s main aim is to find the line that best fits the given data. 2. Here ‘Fitting the best line for given data’ means finding the relation between dependent and independent variables present in the data.   Note 1: you need to use Linear regression only when your dependent and independent variables have linear relationship. Note 2: Here Independent variables can be both discreet or continuous data, but dependent variables should be continuous data. Ok, Let me explain with good example,                                                                    ...

      RESNET Architecture:                   Prerequisites:          VGGNet OR VGG16 :  VGG16 Architecture         DEVELOPED BY MICROSOFT ON 2015 PROBLEM OBSERVED: Regular Neural Networks has a problem that as number of layers increase, even after many epochs the train error and test error of 56 layered Neural Network is worse than the 20 layered Neural Network. source:https://arxiv.org/pdf/1512.03385.pdf Inorder to solve the above problem, The Microsoft team has come up with an idea known as residual unit or identity unit which have skip connection. source:https://arxiv.org/pdf/1512.03385.pdf Basic unit of ResNet Architecture. The above unit is known as either Residual unit or Identity unit. Here the key point is during regularization, if we have unimportant layers then we can avoid them with skip connection. so that there will be no impact on our network. If we ob...

INCEPTION_V3 Prerequisites:  VGGNet OR VGG16:  VGG16 Architecture   By looking it's name, everybody think's that it is a complicated story just like the movie INCEPTION. But trust me, I will prove you that it is wrong by explaining in the most detailed way. Till now, If we take a layer in any neural network we only applied single operation like convolution or maxpooling and also with fixed kernel size for the whole layer.  But Now, The idea is, why can't we use all the operations in a single layer at a time. There comes INCEPTION_V3. Lets zoom a single layer in the inception_v3, source: It's a screenshot from AndrewNg class If you observe the above figure, convolution operation with kernel sizes 1x1,3x3,5x5 and the max-pool operation, all have applied at a time. Here comes a problem, COMPUTATION. only from single layer we are getting billions of computations. For example, lets do a simple mathematical calculation here, Note: To understand this you need to know how c...