Monday, January 23, 2023

Walmart Data Scientist Interview Questions

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What Is The Difference Between A Box Plot And A Histogram

Suman joined Walmart as Data Scientist | Data Scientist Interview | Applied AI Course Reviews

The frequency of a certain features values is denoted visually by both box plots

and histograms.

Boxplots are more often used in comparing several datasets and compared to histograms, take less space and contain fewer details. Histograms are used to know and understand the probability distribution underlying a dataset.

The diagram above denotes a boxplot of a dataset.

My Present Position Does Not Need Me To Work With Data Is It Logical For Me To Pursue This Data Science Certification Program

Data rules businesses all around the world. The more data-driven you are, the better off your company will be. Using data insights, you can make meaningful decisions, create strategies, and help your organization accomplish its goals faster. Enrolling in this comprehensive Data Science curriculum will undoubtedly provide you with a competitive advantage.

Get Ready For Your Next Walmart Data Scientist Interview

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What Is The Eligibility Criteria For This Data Science Certification Program

ThisData Science certification program requires the following qualifications:

  • A bachelor’s degree with a 50% or above grade point average.
  • Understanding basic programming principles and mathematics is required.
  • Working professionals with at least two years of experience are recommended for this Data Science Certification Program.
  • How Should You Maintain A Deployed Model

    Python Programming : The Complete Guide to Learn Python for Data ...

    The steps to maintain a deployed model are:

    Monitor

    Constant monitoring of all models is needed to determine their performance accuracy. When you change something, you want to figure out how your changes are going to affect things. This needs to be monitored to ensure it’s doing what it’s supposed to do.

    Evaluate

    Evaluation metrics of the current model are calculated to determine if a new algorithm is needed.

    Compare

    The new models are compared to each other to determine which model performs the best.

    Rebuild

    The best performing model is re-built on the current state of data.

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    Difference Between Normalisation And Standardization

    Standardization

    Normalization

    • The technique of converting data in such a way that it is normally distributed and has a standard deviation of 1 and a mean of 0.
    • The technique of converting all data values to lie between 1 and 0 is known as Normalization. This is also known as min-max scaling.
    • Standardization takes care that the standard normal distribution is followed by the data.
    • The data returning into the 0 to 1 range is taken care of by Normalization.
    • Normalization formula –

    X = /

    Here,

    Xmin – features minimum value,

    Xmax – features maximum value.

    • Standardization formula –

    X = /

    Differentiate Between Univariate Bivariate And Multivariate Analysis

    Univariate

    Univariate data contains only one variable. The purpose of the univariate analysis is to describe the data and find patterns that exist within it.

    Example: height of students

    The best analogy for selecting features is “bad data in, bad answer out.” When we’re limiting or selecting the features, it’s all about cleaning up the data coming in.

    Wrapper Methods

    This involves:

    • Forward Selection: We test one feature at a time and keep adding them until we get a good fit
    • Backward Selection: We test all the features and start removing them to see what works better
    • Recursive Feature Elimination: Recursively looks through all the different features and how they pair together

    Wrapper methods are very labor-intensive, and high-end computers are needed if a lot of data analysis is performed with the wrapper method.

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    What Is A Bias

    Bias: Due to an oversimplification of a Machine Learning Algorithm, an error occurs in our model, which is known as Bias. This can lead to an issue of underfitting and might lead to oversimplified assumptions at the model training time to make target functions easier and simpler to understand.

    Some of the popular machine learning algorithms which are low on the bias scale are –

    Support Vector Machines , K-Nearest Neighbors , and Decision Trees.

    Algorithms that are high on the bias scale –

    Logistic Regression and Linear Regression.

    Variance: Because of a complex machine learning algorithm, a model performs really badly on a test data set as the model learns even noise from the training data set. This error that occurs in the Machine Learning model is called Variance and can generate overfitting and hyper-sensitivity in Machine Learning models.

    While trying to get over bias in our model, we try to increase the complexity of the machine learning algorithm. Though it helps in reducing the bias, after a certain point, it generates an overfitting effect on the model hence resulting in hyper-sensitivity and high variance.

    Bias-Variance trade-off: To achieve the best performance, the main target of a supervised machine learning algorithm is to have low variance and bias.

    The following things are observed regarding some of the popular machine learning algorithms –

    Want To Land A Job At Walmart

    Varun Patwari Interview Experience at Walmart | Data Scientist Interview | Applied AI Course Reviews

    If youâre looking for guidance as you prepare the Walmart software engineer interview questions, .

    Interview Kickstart offers interview preparation courses taught by FAANG+ tech leads and seasoned hiring managers. We have trained thousands of software engineers to crack the most challenging interviews at Google, Facebook, Amazon, Apple, Netflix, and other top tech companies.

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    How Can You Select K For K

    We use the elbow method to select k for k-means clustering. The idea of the elbow method is to run k-means clustering on the data set where ‘k’ is the number of clusters.

    Within the sum of squares , it is defined as the sum of the squared distance between each member of the cluster and its centroid.

    What Is Pruning In A Decision Tree Algorithm

    In Data Science and Machine Learning, Pruning is a technique which is related to decision trees. Pruning simplifies the decision tree by reducing the rules. Pruning helps to avoid complexity and improves accuracy. Reduced error Pruning, cost complexity pruning etc. are the different types of Pruning.

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    Is This Program Right For Me

    • Applicants must be willing to work in Bentonville, AR or relocate if hired
    • Interested in a Full-Time Data Science role at Walmart starting early 2023
    • Qualifications:
    • Bachelor’s degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years’ experience in an analytics or related field.
    • Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field.
    • 4 years’ experience in an analytics or related field.
  • All applicants welcomed to apply including current Walmart employees
  • What Is An Alias In Sql

    Walmart

    An alias enables you to give a table or a particular column in a table a temporary name to make the table or column name more readable for that specific query. Aliases only exist for the duration of the query.

    The syntax for creating a column alias

    SELECT column_name AS alias_name

    The syntax for creating a table alias

    SELECT column_name

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    You Are Given A Data Set Consisting Of Variables With More Than 30 Percent Missing Values How Will You Deal With Them

    The following are ways to handle missing data values:

    If the data set is large, we can just simply remove the rows with missing data values. It is the quickest way we use the rest of the data to predict the values.

    For smaller data sets, we can substitute missing values with the mean or average of the rest of the data using the pandas’ data frame in python. There are different ways to do so, such as df.mean, df.fillna.

    Learn the fundamentals of Data science for FREE

    What Is The Law Of Large Numbers

    The law of large numbers is a theorem from probability and statistics that suggests that the average result from repeating an experiment multiple times will better approximate the true or expected underlying result. All sample observations for an experiment are drawn from an idealized population of observations.

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    What Are The Benefits Of Using Aws Identity And Access Management

    • AWS Identity and Access Management supports fine-grained access management throughout the AWS infrastructure.

    • IAM Access Analyzer allows you to control who has access to which services and resources and under what circumstances. IAM policies let you control rights for your employees and systems, ensuring they have the least amount of access.

    • It also provides Federated Access, enabling you to grant resource access to systems and users without establishing IAM Roles.

    Facebook Data Science Interview Questions

    Walmart Data Science Case Study Mock Interview: Underpricing Algorithm

    1) A building has 100 floors. Given 2 identical eggs, how can you use them to find the threshold floor? The egg will break from any particular floor above floor N, including floor N itself.

    2) In a given day, how many birthday posts occur on Facebook?

    3) You are at a Casino. You have two dices to play with. You win $10 every time you roll a 5. If you play till you win and then stop, what is the expected pay-out?

    4) How many big Macs does McDonald sell every year in US?

    5) You are about to get on a plane to Seattle, you want to know whether you have to bring an umbrella or not. You call three of your random friends and as each one of them if its raining. The probability that your friend is telling the truth is 2/3 and the probability that they are playing a prank on you by lying is 1/3. If all 3 of them tell that it is raining, then what is the probability that it is actually raining in Seattle.

    6) You can roll a dice three times. You will be given $X where X is the highest roll you get. You can choose to stop rolling at any time . What is your expected pay-out?

    7) How can bogus Facebook accounts be detected?

    8) You have been given the data on Facebook users friending or defriending each other. How will you determine whether a given pair of Facebook users are friends or not?

    9) How many dentists are there in US?

    10) You have 2 dices. What is the probability of getting at least one 4? Also find out the probability of getting at least one 4 if you have n dices.

    New Projects

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    What Challenges Came Up During Your Recent Project And How Did You Overcome These Challenges

    Any employer wants to evaluate how you react during difficulties and what you do to address and successfully handle the challenges.

    When you talk about the problems you encountered, frame your answer using the STAR method:

    • Situation: Brief them about the circumstances due to which problem occurred.
    • Task: It is essential to elaborate on your role in overcoming the problem. For example, if you took a leadership role and provided a working solution, then showcasing it could be decisive if you were interviewing for a leadership position.
    • Action: Walk the interviewer through the steps you took to fix the problem.
    • Result: Always explain the consequences of your actions. Talk about the learnings and insights gained by you and other stakeholders.

    What Are The Differences Between The Programming Languages: C And C++

    • C language: C is a widely-used general-purpose programming language that is easy to learn and use. It is a machine-independent structured programming language that is widely used to create a variety of applications, operating systems such as Windows, and other complicated programs such as the Oracle database, Git, Python interpreter, and others. C can be considered a programming foundation. You can readily understand the knowledge of other programming languages that employ the concept of ‘C’ if you know ‘C.’
    • C++ language: C++ is a general-purpose programming language. It has been developed in an effort to improvise over the C language. C++ programming language aims to include an object-oriented paradigm. C++ is an imperative programming language. It is a middle-level programming language and it can therefore be used to program both low-level programs such as drivers, kernels and higher-level programs such as games, GUI, desktop apps and so on. C++ has a similar code syntax as that of C.

    The following table lists the differences between C and C++ programming languages:

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    Google Data Science Interview Questions

    1) Explain about string parsing in R language

    2) A disc is spinning on a spindle and you dont know the direction in which way the disc is spinning. You are provided with a set of pins.How will you use the pins to describe in which way the disc is spinning?

    3) Describe the data analysis process.

    4) How will you cut a circular cake into 8 equal pieces?

    Have You Worked With Etl If Yes Please State Which One Do You Prefer The Most And Why

    Secrets to a Successful Data Science Interview

    With this question, the recruiter needs to know your understanding and experience regarding the ETL tools and process. You should list all the tools in which you have expertise and pick one as your favourite. Point out the vital properties which make that tool stand out and validate your preference to demonstrate your knowledge in the ETL process.

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    What Is The Difference Between The Long Format Data And Wide Format Data

    LONG FORMAT DATA: It contains values that repeat in the first column. In this format, each row is a one-time point per subject.

    WIDE FORMAT DATA: In the Wide Format Data, the datas repeated responses will be in a single row, and each response can be recorded in separate columns.

    Long format Table:

    Why Apply To The Program

    Immediate Job Opportunities at Walmart

    Walmart Global Tech will be ready to interview you upon successful completion of the program. As a Walmart Global Tech data scientist, you can expect beyond competitive pay, incentive awards, 401 match, stock purchase plan, paid maternity and parental leave, PTO, multiple health plans, associate discounts, and much more!

    World-Class Data Science Training

    Correlation One is the market leader in Data Science and Analytics Training. You will learn through a novel blend of case-based, instructor-led lessons, collaborative group work in teams, and real-time support from experts in the field- 100% virtually

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    What Information Is Gained In A Decision Tree Algorithm

    Information gain is the expected reduction in entropy. Information gain decides the building of the tree. Information Gain makes the decision tree smarter. Information gain includes parent node R and a set E of K training examples. It calculates the difference between entropy before and after the split.

    What You’ll Do As A Data Scientist At Walmart

    SQL Interview Question asked by Walmart Company | Data Science Interview Question

    Data Scientists at Walmart Global Tech specialize in applying machine learning and artificial intelligence to solve problems across Merchandising, Supply chain, Operations, Real estate and eCommerce.

    You will have the opportunity to work with a high caliber team from a variety of disciplines to build new software and radically change the business. Data Scientists work as part of an Experience Team to develop and deploy advanced algorithms at scale.

    You will support and enable the entire project lifecycle including problem discovery with business clients, algorithmic design, coding, validation, deployment, testing, and monitoring. Data Scientists adhere to agile software development standards through rapid prototyping, iterative development, and incremental deployment of capabilities. Development is performed in Sprints and Data Scientists are held accountable to engineering excellence standards.

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    What Do You Understand By Wild Pointers How Can That Be Avoided

    Wild pointers are uninitialized pointers that point to any arbitrary memory location, potentially causing a program to crash or behave improperly.

    Example – Let us consider the following C program:

    int main

    In the above example, no memory location is defined for the pointer temp_pointer and hence it is a wild pointer. Any random memory location will be assigned to such a pointer and this may corrupt the data present previously on that memory location.

    To avoid this, if we want to declare a pointer and we do not have a variable to which we can point the pointer, we can do the following:

    int main

    In the above example, we made the pointer temp_pointer point to a memory location explicitly allocated for the pointer. This eliminates the risk of corrupting any random memory location.

    What Are The Various Types Of Load Balancers Available In Aws

  • An Application Load Balancer routes requests to one or more ports on each container instance in your cluster, making routing decisions at the application layer . It also enables path-based routing and may route requests to one or more ports on each container instance in your cluster. Dynamic host port mapping is available with Application Load Balancers.

  • The transport layer is where a Network Load Balancer decides the routing path. It processes millions of requests per second, and dynamic host port mapping is available with Network Load Balancers.

  • Gateway Load Balancer distributes traffic while scaling your virtual appliances to match demands by combining a transparent network gateway.

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