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Reading list

Machine Learning Basics for a Newbie
6 Steps of Machine learning Lifecycle Introduction to Predictive Modeling
Introduction to Exploratory Data Analysis & Data Insights Descriptive Statistics Inferential Statistics How to Understand Population Distributions?
Reading Data Files into Python Different Variable Datatypes
Probability for Data Science Basic Concepts of Probability Axioms of Probability Conditional Probability
Central Tendencies for Continuous Variables Spread of Data KDE plots for Continuous Variable Overview of Distribution for Continuous variables Normal Distribution Skewed Distribution Skeweness and Kurtosis Distribution for Continuous Variable
Central Tendencies for Categorical Variables Understanding Discrete Distributions Performing EDA on Categorical Variables
Dealing with Missing Values Understanding Outliers Identifying Outliers in Data Outlier Detection in Python Outliers Detection Using IQR, Z-score, LOF and DBSCAN
Sample and Population Central Limit Theorem Confidence Interval and Margin of Error
Bivariate Analysis Introduction
Covariance Pearson Correlation Spearman's Correlation & Kendall's Tau Correlation versus Causation Tabular and Graphical methods for Bivariate Analysis Performing Bivariate Analysis on Continuous-Continuous Variables
Tabular and Graphical methods for Continuous-Categorical Variables Introduction to Hypothesis Testing P-value Two sample Z-test T-test T-test vs Z-test Performing Bivariate Analysis on Continuous-Catagorical variables
Chi-Squares Test Bivariate Analysis on Categorical Categorical Variables
Multivariate Analysis A Comprehensive Guide to Data Exploration The Data Science behind IPL
Supervised Learning vs Unsupervised Learning Reinforcement Learning Generative and Descriminative Models Parametric and Non Parametric model
Machine Learning Pipeline Preparing Dataset Build a Benchmark Model: Regression Build a Benchmark Model: Classification
Evaluation Metrics for Machine Learning Everyone should know Confusion Matrix Accuracy Precision and Recall AUC-ROC Log Loss R2 and Adjusted R2
Dealing with Missing Values Replacing Missing Values Imputing Missing Values in Data Working with Categorical Variables Working with Outliers Preprocessing Data for Model Building
Understanding Cost Function Understanding Gradient Descent Math Behind Gradient Descent Assumptions of Linear Regression Implement Linear Regression from Scratch Train Linear Regression in Python Implementing Linear Regression in R Diagnosing Residual Plots in Linear Regression Models Generalized Linear Models Introduction to Logistic Regression Odds Ratio Implementing Logistic Regression from Scratch Introduction to Scikit-learn in Python Train Logistic Regression in python Multiclass using Logistic Regression How to use Multinomial and Ordinal Logistic Regression in R ? Challenges with Linear Regression Introduction to Regularisation Implementing Regularisation Ridge Regression Lasso Regression
Introduction to K Nearest Neighbours Determining the Right Value of K in KNN Implement KNN from Scratch Implement KNN in Python
Bias Variance Tradeoff Introduction to Overfitting and Underfitting Visualizing Overfitting and Underfitting Selecting the Right Model What is Validation? Hold-Out Validation Understanding K Fold Cross Validation
Introduction to Feature Selection Feature Selection Algorithms Missing Value Ratio Low Variance Filter High Correlation Filter Backward Feature Elimination Forward Feature Selection Implement Feature Selection in Python Implement Feature Selection in R
Introduction to Decision Tree Purity in Decision Tree Terminologies Related to Decision Tree How to Select Best Split Point in Decision Tree? Chi-Squares Information Gain Reduction in Variance Optimizing Performance of Decision Tree Train Decision Tree using Scikit Learn Pruning of Decision Trees
Introduction to Feature Engineering Feature Transformation Feature Scaling Feature Engineering Frequency Encoding Automated Feature Engineering: Feature Tools
Introduction to Naive Bayes Conditional Probability and Bayes Theorem Introduction to Bayesian Adjustment Rating: The Incredible Concept Behind Online Ratings! Working of Naive Bayes Math behind Naive Bayes Types of Naive Bayes Implementation of Naive Bayes
Understanding how to solve Multiclass and Multilabled Classification Problem Evaluation Metrics: Multi Class Classification
Introduction to Ensemble Techniques Basic Ensemble Techniques Implementing Basic Ensemble Techniques Finding Optimal Weights of Ensemble Learner using Neural Network Why Ensemble Models Work well?
Introduction to Stacking Implementing Stacking Variants of Stacking Implementing Variants of Stacking Introduction to Blending Bootstrap Sampling Introduction to Random Sampling Hyper-parameters of Random Forest Implementing Random Forest Out-of-Bag (OOB) Score in the Random Forest IPL Team Win Prediction Project Using Machine Learning Introduction to Boosting Gradient Boosting Algorithm Math behind GBM Implementing GBM in python Regularized Greedy Forests Extreme Gradient Boosting Implementing XGBM in python Tuning Hyperparameters of XGBoost in Python Implement XGBM in R/H2O Adaptive Boosting Implementing Adaptive Boosing LightGBM Implementing LightGBM in Python Catboost Implementing Catboost in Python
Different Hyperparameter Tuning methods Implementing Different Hyperparameter Tuning methods GridsearchCV RandomizedsearchCV Bayesian Optimization for Hyperparameter Tuning Hyperopt
Understanding SVM Algorithm SVM Kernels In-depth Intuition and Practical Implementation SVM Kernel Tricks Kernels and Hyperparameters in SVM Implementing SVM from Scratch in Python and R
Introduction to Principal Component Analysis Steps to Perform Principal Compound Analysis Computation of Covariance Matrix Finding Eigenvectors and Eigenvalues Implementing PCA in python Visualizing PCA A Brief Introduction to Linear Discriminant Analysis Introduction to Factor Analysis
Introduction to Clustering Applications of Clustering Evaluation Metrics for Clustering Understanding K-Means Implementation of K-Means in Python Implementation of K-Means in R Choosing Right Value for K Profiling Market Segments using K-Means Clustering Hierarchical Clustering Implementation of Hierarchial Clustering DBSCAN Defining Similarity between clusters Build Better and Accurate Clusters with Gaussian Mixture Models
Understand Basics of Recommendation Engine with Case Study
8 Ways to Improve Accuracy of Machine Learning Models
Introduction to Dask Working with CuML
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to Machine Learning Interpretability Framework and Interpretable Models model Agnostic Methods for Interpretability Implementing Interpretable Model Understanding SHAP Out-of-Core ML Introduction to Interpretable Machine Learning Models Model Agnostic Methods for Interpretability Game Theory & Shapley Values
Introduction to AutoML Implementation of MLBox Introduction to PyCaret TPOT Auto-Sklearn EvalML
Pickle and Joblib Introduction to Model Deployment
Deploying Machine Learning Model using Streamlit Deploying ML Models in Docker Deploy Using Streamlit Deploy on Heroku Deploy Using Netlify Introduction to Amazon Sagemaker Setting up Amazon SageMaker Using SageMaker Endpoint to Generate Inference Deploy on Microsoft Azure Cloud Introduction to Flask for Model Deploying ML model using Flask
Model Deployment in Android Model Deployment in Iphone

Top 9 Must Read Spring Boot Interview Questions

Vibha
Vibha Last Updated : 09 Jan, 2023
5 min read

This article was published as a part of the Data Science Blogathon.

Spring Boot
Source:javaguides.net

Introduction

Spring Boot is an application developed on top of the Spring Framework. It makes it simpler and faster to install, set up, and execute both basic and web-based apps.

The Spring module provides the Spring Framework with the RAD (Rapid Application Development) capability. It is used to develop a standalone Spring-based application that may be executed without any Spring settings.

If you are attending a job interview and are searching for a list of spring boot interview questions and answers, you have arrived at the correct spot. This article contains a list of interview questions and answers for both experienced and inexperienced candidates, which will help you land your desired job. Here we go.

Why Should You Use Spring Boot?

Increases Productivity

Spring Boot dramatically simplifies Java programming. Spring Boot’s application environment and integrated web server make microservice development easy. To deploy microservices-based architectures at record speed and integrate it with Spring Cloud’s libraries, servers, patterns, and templates.

Fast Speed

Spring Boot features a quick startup, a quick shutdown, and streamlined execution by default. Spring projects increasingly embrace the reactive (nonblocking) programming approach for improved efficiency. Developer efficiency is Spring’s greatest strength. Spring Boot facilitates the development of apps with far less effort than other competing paradigms. Embedded web servers, auto-configuration, and “fat jars” facilitate a speedy start.

Security

Spring Boot handles security concerns swiftly and responsibly. Spring committers fix and test reported vulnerabilities with security experts. Regular updates help keep your data and apps safe by monitoring third-party dependencies. Spring Security helps you integrate industry-standard security schemes and offer secure-by-default solutions.

1. What is Spring Cloud?

Spring Cloud is an open-source package that provides tools for efficiently deploying JVM-based applications to cloud environments. Because of features like Distributed configuration, Circuit breakers, Global locks, Service registrations, Load balancing, Cluster state, Routing, Load Balancing, and so on, it gives a better user experience and an expandable mechanism. It can operate with spring and many apps written in various languages.

Spring Boot
Source: educba

The following are the main features:

  • Distributed Messaging
  • service-to-service calls
  • Circuit breakers
  • Global locks
  • Service registration
  • Service Discovery
  • Load balancing
  • Cluster state
  • Routing

2. Mention the Benefits of Spring Boot.

Benefits of a Spring Boot –

  • It supports convention over configuration. Thus, you may completely bypass XML configuration.
  • SpringBoot helps to enhance productivity by reducing development time.
  • Reduces the amount of boilerplate code in your program.
  • It includes integrated HTTP servers like Tomcat, Jetty, etc, for developing and testing your applications.
  • It includes a CLI (Command Line Interface) tool too that helps you to design and test your application from the command line.

3. What Features do Spring Boots Have?

The following are some of the important spring boot features:

  • Springboot’s admin support function is used to administer applications remotely and also gives the ability to activate admin-related capabilities for the application.
  • Spring Boot’s externalized configuration enables developers to work with the same application code in multiple environments.
  • Springboot’s profile functionality helps you to separate portions of your application and make them exclusively visible in specific settings.
  • Springboot’s logging functionality uses “Commons Logging” for all internal logging.
  • Springboot’s internationalization functionality supports translated messages, providing your application to accommodate diverse language preferences.
  • It integrates three JSON libraries: Gson, Jackson, and JSON-B.
  • It is one of the platforms that is highly suited for web applications.
  • By default, it is secure, providing basic authentication on all HTTP endpoints.

4. What is Spring Boot’s Main Dependencies?

The following are important Spring Boot dependencies that should be introduced to a Gradle or Maven-based application to ensure compatibility with its capabilities.

Spring Boot
Source: techblogstation.com

 

  • spring-boot-starter-parent
  • spring-boot-maven-plugin
  • spring-boot-starter-test
  • spring-boot-starter-security
  • spring-boot-starter-actuator
  • spring-boot-starter-web

5. How to Fix the Whitelabel Error Page in a Spring Boot Application?

whitelabel
Source: blogspot.com

This error, 404, is highly common in spring boot applications (page not found).

This can be resolved in three ways:

  • Custom Error Controller – where you implement the ErrorController interface provided by SpringFramework and then override its getErrorPath() function to deliver a custom route whenever an error of this type occurs.
  • By Displaying a Custom Error Page – Create an error.html file and insert it in the src/main/resources/templates directory. Springboot’s BasicErrorController will automatically select this file by default.
  • By deactivating the Whitelabel error page – By setting the server.error.whitelabel.enabled parameter to be false in the application.properties file, you may deactivate the whitelabel error page. This is the easiest way.

6. What differentiates Spring Boot from JAX-RS?

Users can get considerable advantages over JAX-RS by using functionalities, like:

  • Rapid deployment
  • Scalability is excellent.
  • Compatibility with containers
  • Minimalist design
  • Reduced manufacturing time
  • Productivity has increased.
  • Shortened development time
  • Applications can be easily monitored and managed.

7. What do you Think About Starters in Spring Boot?

Starters are similar to launchers in that they provide a collection of dependencies that may be incorporated into the application. You may combine Spring and other technologies in one spot rather than searching, for example, code and dependencies all over the place. To use Spring JPA to access the database, just add the spring-boot-starter-data-JPA launcher requirement. Starters include dependencies that are required by many projects. They are a collection of supported management transitive dependencies that execute swiftly and constantly.

8. Discuss the Advantages of the YAML file over the Properties file, And Several Ways to Load the YAML File in Spring Boot.

YAML provides better clarity and is highly user-friendly. Maps, lists, and other scalar types are supported too. The hierarchical design of YAML helps eliminate repetition and indentations.

Suppose we have several deployment profiles, like development, testing, or production, and we may have different settings for each environment. In that case, we may store them in a single YAML file instead of creating separate files for each environment.

However, you cannot do so using the properties file.

Example:

spring:
profiles:
active:
-test
---
spring:
profiles:
active:
-prod
---
spring:
profiles:
active:
-development

9. What is the Difference Between the @RestController and @Controller Annotations?

The traditional Spring @Controller annotation indicates that a class is marked as a controller. It’s essentially a @Component specialization that is identified automatically through classpath scanning. The @Controller annotation is used in conjunction with @RequestMapping annotated handler procedures. Developers use the @RestController annotation to create RESTful web services with the Spring Model-View-Controller framework (MVC). Spring @RestController transfers request data to request handler functions. The @RestController converts the response body to XML or JSON once the handler function creates it.

controller and rest controller

Source: Medium

Conclusion

This article provides information on Spring Boot, a sub-project of Spring’s open-source organization. It provides a one-stop shop for Spring components. It simplifies the process of using Spring. It saves a lot of settings and has a variety of launchers to help developers get started quickly. Along with the stated topics, all levels of interview questions are covered:

  • What exactly is Spring Boot, and why should we use it?
  • Its Benefits and Features
  • Resolving the whitelabel error page
  • Spring Cloud, Straters, YAML Files, and so on.

We hope this blog post has helped you familiarize yourself with commonly asked spring boot interview questions. These frequently asked interview questions might help you refine your abilities and ace your next interview.

The media shown in this article is not owned by Analytics Vidhya and is used at the Author’s discretion.

Vibha
Vibha

I am an engineering student. Currently, I am pursing Btech from Vellore Institute of Technology. I am very passionate about programming and constantly eager to expand my knowledge in Data Science and Machine Learning.

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