## Joins in SQL | Data Science Quiz | Day 3/30

We will concentrate on Joins in SQL on the third day of our quiz. Data Science has a lot to do with SQL and in your DS interviews, Joins in SQL will occupy a lot of time

Continue readingLost your password? Please enter your email address. You will receive a link and will create a new password via email.

It will take less than 1 minute to register for lifetime. Bonus Tip - We don't send OTP to your email id Make Sure to use your own email id for free books and giveaways

Create an account

We will concentrate on Joins in SQL on the third day of our quiz. Data Science has a lot to do with SQL and in your DS interviews, Joins in SQL will occupy a lot of time

Continue readingSQL interview questions - Day 2 of the quiz will have most of the questions from SQL Bread and Butter of a Data Scientist/Analyst

Continue readingWe will be doing Data Science interview questions on a daily basis. So you will be receiving 10 Data Science interview questions for the next 30 days on topics like SQL, Python, Case Studies, Machine Learning, Statisti

Continue readingHere we have a set of 17 statistics interview questions that you should understand before your data science interviews. These are very basic Statistics questions which will check your elementary knowledge

Continue readingPeople have always been curious about how to make a career in data science or how to enter this domain after an experience of, say 3-4 years.We will help you in providing Data Science preparation strategyShould I do ...

Continue readingThe first step for any time series analysis is to make the data set stationary. Everyone knows that stationarity means a near to constant mean and variance across time.

Continue readingThe first mistake we do while starting Python for Data Science is to start like a Programmer. Firstly, make sure about how are you going to use Python in your career?If you want to be a Software Engineer ...

Continue readingIn our datasets we can have any sort of data, we can have numbers, categories, texts, or literally anything. If you have ever created any model , you already know that you can't use Textual Data to train ...

Continue readingThe target is to complete all 800 words in this lock down, we are already at 320 and will be closing at 350 tonight. And we have another 14 days, so the aim should be to cover 30 ...

Continue readingR is one of the two most popular Data Science programming language. If you are new to this domain, then we would always recommend you to start with R because of it's easier installation steps, minimal version control, ...

Continue readingYeah !!Day 12 is here :)I did not know that these posts have a 'small' following :)Thank you guys Let's start and end it in this lock down295. abject - miserable; pitifulWhen Shobha rejected Rajesh, Rajesh felt abject296. ...

Continue readingProbably you have a lot of information about what to study and not to study for a Data Science job. But, when you start applying to a DS job, then you will realize that the whole process contains ...

Continue readingData Science is one of those domains which are less explored in colleges but is in high demand in the I.T. sector.The combination of Maths and Technology makes it even more interesting. I have been working as a ...

Continue readinginstall.packages("stringr")library(stringr) data = read.csv("C:/Users/User/Desktop/Hackathon/JantaHack/train.csv")head(data)str(data) data$product <- str_count(data$ProductList,";")+1head(data)data$hours <- with(data, difftime(endTime,startTime,units="hours") )data$min <- with(data, difftime(endTime,startTime,units="mins") )data$x <- as.double(data$endTime - data$startTime, units = "mins") table(data$product)hist(data$product) table(data$gender)count <- table(data$gender,data$product)barplot(count)str(data)head(data$ET)head(data$endTime)

Continue readingMissing Value treatment is no doubt one of the most important parts of the whole process of building a model. Why?Because we can't afford to eliminate rows wherever there is a missing value in any of the columns. ...

Continue readingWhy do we predict?We predict in order to identify the trend of the future by using our sample data set. Whenever we create a model, we try to create a formula out of our sample data set. And ...

Continue readingToo much work in WFH :PWas already dozing, but let's end the day with at least a few words in hand. Let's go 281. quorum - Number of member necessary to conduct a meetingTo start ...

Continue readingWe all know the definition of multi-collinearity i.e. when 2 or more explanatory variable in multi regression model are highly linearly related then it's called multicollinearityExample - Age and Selling price of a CarEducation and Annual IncomeHeight and ...

Continue readingWe are already good with 220 words, lets's pass that 250 mark. All the words given below are directly from Barron's 800 most frequent words. 251. abeyance - temporary suspensionIf you have ever created an ...

Continue readingSQL is the bread and butter of an analyst. You can't survive in the Data Science industry with a grip on this 'easy-looking' query language. I have been interviewed for more than 30 companies in the past 3-4 ...

Continue readingI was onto our next book - Linear,Ridge, LAASO, and Elastic Net Algorithm explained in layman terms with code in R , when we thought of covering the simple concepts which are quite helpful while creating models.Cross Validation ...

Continue readingRidge and LASSO are two important regression models which comes handy when Linear Regression fails to work.This topic needed a different mention without it's important to understand COST function and the way it's calculated for Ridge,LASSO, and any ...

Continue readingBarron's 800 most frequent words are one of the best consolidated list of words which is asked/referred in GRE/GMAT.Also, this is a personal practice. You can DEFINITELY comment your way of learning a particular word :)Let's start Day ...

Continue readingLinear,LASSO, Elastic Net, and Ridge Regression are the four regression techniques which are helpful to predict or extrapolate the prediction using the historic data. Linear doesn't have any inclination towards the value of lambda.LASSO takes ...

Continue readingToday we will cross the 25% mark and you would have already covered 200+ most frequently used words from Barron's 800191. abdicate - to give up a positionIt sounds like vacate, right?The govt. was accused of abdicating ...

Continue readingIt's such a beautiful day, I already learnt 30 words and I would like to continue. Let's learn Barron's 800 words for GRE in the most layman and simple way 161. emollient - mollify; soothingAt ...

Continue readingLearn Barron 800 words in simple and layman way for GREWe will start with 133 and will learn a lot of words today133. Abscission - Act of cutting; the natural separation of a leaf or other part of ...

Continue readingSo, I just started solving the latest Hackathon on Analytics Vidhya, Women in the loop . Be it a real-life Data Science problem or a Hackathon, one-hot encoding is one of the most important part of ...

Continue readingYou should revise the previous 120 words first !!But no one follows the rule, so let's proceed :PToday will we be 150 words strong :)121. aberrant - deviating from what is normalImagine, there is a line of ants ...

Continue readingTarget 330We have already covered 90 words i.e. more than 10% of the word list. Let's make it 15% today91. audacious - boldYou know where did I always hear this word?I hear it from Ravi Shashtri, "This is ...

Continue readingTarget 330Disclaimer - I have used all the references to remember the meaning of the words. There are a few very naive ways down there. So, please ignore61. abscond - to depart secretlyOne of the classic example of ...

Continue readingTarget 33031. Vendetta - prolonged bitter quarrel against someoneRemember the movie V for Vendetta ?Vendetta means a prolonged bitter quarrel against someone.I have not watched the movie but I guess there was a story in Bollywood where Amir ...

Continue readingAim – 160+ in GREResources – Barron’s 800 and 100 RCsB.S – It stands for Bullshit StoryDay 11. Abate – to decreaseAfter a 15 days of lockdown, the Corona virus cases suddenly abated, bringing smile and relief on everyone’s ...

Continue readingHave you ever wondered why two different people gets different accuracy while using the same algorithm?We all know that XGBoost can help us get a very good result in our Hackathons, but then also only few people achieve ...

Continue readingCorrelation tells you have two numerical variables relate to each other. It will tell you whether data points that have a higher than average value for one variable will also likely have a higher than average value for ...

Continue readingForecasting and Prediction are two different things. You always forecast weather, but never predict the weather. Forecasting is nothing but a extrapolation of the past. You have some historic data, and you ...

Continue readingp-value in simple termsIf you are into Data Science, then you must have heard about p-value.I could have started it with a very superficial definition strolling around probability and significance and null hypothesis, etc. But that's already there ...

Continue readingWhat is Confusion Matrix?Confusion Matrix is a performance measuring technique for ML Classification model.Why do we need Confusion Matrix? Is measuring accuracy not enough?Confusion Matrix suggests the actual accuracy of your model. For example. Suppose I want to ...

Continue readingWe often come across few terms which sounds no different but are poles apart. The same goes with Data Science, Big Data,Data Analytics, and Business Analyst. So if you are confused about the role which an employer is ...

Continue readingThe below article is the intellectual property of Ashish Kohli. This is one such article which actually powers the ability of SQL. Give it a read guys. Yes, you read that one right! One ...

Continue readingCompany - Affine AnalyticsLocation - BangalorePosition - Senior Business AnalystExperience - 3+ yearsCompensation - Best in the industry Affine Analytics Interview Questions

Continue reading1. What if you want to toggle case for a Python string? We have the swapcase() method from the str class to do just that. 1. >>> 'AyuShi'.swapcase() ‘aYUsHI’

Continue reading1.How would you convert a string into an int in Python? If a string contains only numerical characters, you can convert it into an integer using the int() function. >>> int('227') ...

Continue reading1.What will the following code output? >>> word=’abcdefghij’ >>> word[:3]+word[3:] The output is ‘abcdefghij’. The first slice gives us ‘abc’, the next gives us ‘defghij’. 2.How ...

Continue readingThis is something which has been on my mind since a long time. We will be picking 10 questions per day and would like to simplify it.We will make sure that the complete article is covered in 10 ...

Continue readingThis is something which has been on my mind since a long time. We will be picking 10 questions per day and would like to simplify it.We will make sure that the complete article is covered in 10 ...

Continue readingQ1. What are the parts of Microsoft self-service business intelligence solution? Microsoft has two parts for Self-Service BI Excel BI Toolkit It Allows ...

Continue readingQ1. What is a Sample? A. A data sample is a set of data collected and the world selected from a statistical population by a defined procedure. The elements of a sample are known as sample points, sampling units or observations. Q2. Define Population.

Continue readingYou can assume anything and everything under the Sun, just to try to keep the assumptions close to realityI always start with an equation, for this question the ...

Continue readingAns: Let’s assume population of Bangalore as 10 million and the day today is a working day for every age group And age group wise population ...

Continue reading