Saurabh Parab

- By Saurabh Parab It is possible to cut back  While more than a third of Indians are worried about their finances as a result of the COVID-19 crisis, others have experienced a significant boost to savings. At the end of the day, it's all about the mentality. Whether you want to believe it or not, lockdown because of the COVID-19 pandemic has led to savings that are othe rwise not noticed by us. Inability to save, worries about economic conditions, and the struggle to pay household bills are the top concerns of Indian adults during the lockdown. But while many households are struggling, some have been able to save more than usual in recent months.  Why? Perhaps because we’re spending less. Ahold on holidays and Movies.   Unsurprisingly, spending on non-essential items fell as a result of government-imposed lockdown. So, Indirectly the government is giving us the people some guidance about money savings. Sarcasm!!!, Anyways Analysts suggests that a typical Indian household could be

 Netflix probably has become your go-to application when bored in this quarantine. So it's not surprising that it picked up nearly 16 million global subscribers during the first three months of the year, helping cement its status as one of the world's most essential services in times of isolation or crisis. As of April 2020, Netflix had over 193 million paid subscriptions worldwide, including 73 million in the United States It is available worldwide except  China, DPRK (North Korea), Crimea.  So let's do some analysis on Netflix Following is the content distribution of  Netflix. ( shown in the form of a pie chart ) Next up let's compare the two powerhouses against each other i.e USA and India. As you can see the number of movies and tv shows added by the USA is constantly increasing whereas in India there's a slight decline in the addition of movies and the number of tv shows has remained constant. Viewing Time vs Hours per daily The entire world is streaming more t

  What are Outliers?? Outliers are defined as samples that are significantly different from the remaining data. Those are points that lie outside the overall pattern of the distribution. Statistical measures such as mean, variance, and correlation are very susceptible to outliers. A simple example of an outlier is here, a point that deviates from the overall pattern. Outliers can occur in the dataset due to one of the following reasons:- 1. Genuine extreme high and low values in the dataset 2. Introduced due to human or mechanical error 3. Introduced by replacing missing values. In some cases, the presence of outliers are informative and will require further study. For example, outliers are important in use-cases related to transaction management where an outlier might be used to identify potentially fraudulent transactions. How to Detect Outliers?? 1.Extreme Value Analysis by BoxPlot  2.K Means clustering-based approach 3.Visualizing the data How to Treat Outliers? 1.Mean/Median or ra

We discussed the Linear Regression concept in the previous blog with a Layman example. So, let's discuss the Linear Regression model and its mechanism. Linear Regression model makes use of two sets of variables:- Independent variables (termed as x ) Dependent variable(termed as y) Independent variables are the ones that are used to predict(calculate) the dependent variable. If we take into consideration an example from the previous blog, then the independent variable will be 'Kilometers' and the dependent variable will be "Amount". So in a nutshell:- You are predicting the amount based on the kilometers .i.e 'if I want travel x km then how much will it cost me (Y)?   Linear Regression can be further broken down into two types:-  Simple Linear Regression   Multiple Linear Regression   Simple Linear Regression is the one we just discussed above where we have one independent variable (km) and based on that we have to predict the dependent variable (Amount). Multi