TOP 10 FREQUENTLY ASKED MACHINE LEARNING INTERVIEW QUESTIONS

 This article will take you through the top 10 frequently asked machine learning interview questions.

Companies are using new-age technologies like artificial intelligence (AI) and machine learning (ML) to make information and services more accessible to users. These technologies are being increasingly adopted in industries such as banking, finance, retail, manufacturing, healthcare, and more. Some of the in-demand organizational jobs that are adopting AI include data scientists, artificial intelligence engineers, Machine learning Engineers, and data analysts. If you want to apply for jobs like these, you should be aware of the sorts of machine learning interview questions that recruiters and hiring managers could ask. This article guides you through some of the most common machine learning interview questions and answers you’ll come across on your journey to landing your ideal job.

1. 

Explain what artificial intelligence (AI), machine learning (ML), and deep learning are and what they mean.

2 . 

What are the different types of machine learning?

3.

Make a distinction between data mining and machine learning.

4. 

What is the difference between deep learning and machine learning?

5. 

What is overfitting in machine learning? Why does it occur and how can you stay away from this?

6. 

In machine learning, what is a hypothesis?

7.

In machine learning, what is Bayes’ theorem?

8. 

What is cross-validation in machine learning?

9.

What is entropy in machine learning?

10. 

What is the epoch in machine learning?

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TOP 10 AFFORDABLE COUNTRIES TO STUDY DATA SCIENCE

 

You can’t miss this list of countries if you are data science passionate and want to enhance your skills.

Data science is the trendiest and the most in-demand course to follow up in 2021. With millions of qubits of data produced every day, it is really important to cater to the number of data scientists and analysts to analyze, interpret, organize and distribute data. But more often than not in countries like the USA and UK, pursuing data science becomes really difficult to afford. So here we at Analytics Insight churned up the whole world’s universities and colleges and countries to bring to you the top 10 affordable countries to study data science in the world.

1. India

(The average cost of the course would be around 20,000 – 5,00,000 INR)

2. Norway

(Study Costs in Norway

Tuition Fees: FREE

Living Expenses: NOK 116,369 (appx. INR 9 – 10 Lacs) per year.)

3. Germany

(Study Costs in Germany

Tuition Fees: EUR 125 – EUR 1,500 per semester | INR 20,000 – 2 Lacs per year

Living Expenses: EUR 650 – 800 per month | appx. INR 6.5 – 8 Lacs per year.)

4. Switzerland

(Tuition Fees: CHF 500 – 2,000 per semester | INR 1.2 Lacs – 4 Lacs per year

Living Expenses: CHF 1,400 – 1,800 per month | INR 10 – 14 Lacs per year.)

4. Denmark

(Tuition Fees: DKK 45,000 – DKK 120,000 per year | INR 4.5 Lacs to 12 Lacs per year

Living Expenses: DKK 6,000 – DKK 10,000 per month | INR 7.5 Lacs – INR 11 Lacs per year.)

5. Belgium

(Tuition Fees: EUR 900 – EUR 4,000 per year | INR 70,000 – INR 3.5 Lacs per year

Living Expenses: EUR 700 – EUR 1,200 per month | INR 7 – 11 Lacs per year.)

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TOP 10 BUSINESS INTELLIGENCE AND ANALYTICS PROVIDERS IN INDIA

 

Today, all organization’s decisions and processes are driven by digitization and data analysis. Collecting data from digital systems and analyzing it is the key to making sophisticated and intelligent decisions for business organizations. With digital transformation, businesses rely on big data and data science to enhance efficiency and this has increased the demand for business intelligence and business analytics solutions thus encouraging the need for business intelligence and business analytics companies to emerge.

Indian business intelligence companies provide business reporting solutions that are all-inclusive, reasonably priced, and simple to understand, implement, organize and maintain. Most BI products offered by these firms are next-generation reporting solutions constructed from modern technology and processes. Here is the list of the top 10 business intelligence and analytics companies in India.

1. Teradata Corporation ( Located in around 40 nations )

2. MAIA Intelligence

3. Binary Semantics Ltd

4. IDC India Ltd.

5.TechAxes

6. Fractal

7. Manthan

8. Latent View (Based in New Jersey, Latent View has its Indian operations in Mumbai and Chennai.)

9. Tiger Analytics

10. Absolut Data

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Big Data Analytics Tutorial

 The volume of data that one has to deal with has exploded to unimaginable levels in the past decade, and at the same time, the price of data storage has systematically reduced. Private companies and research institutions capture terabytes of data about their users’ interactions, business, social media, and also sensors from devices such as mobile phones and automobiles. The challenge of this era is to make sense of this sea of data. This is where big data analytics comes into the picture.

Big Data Analytics largely involves collecting data from different sources, munge it in a way that it becomes available to be consumed by analysts, and finally deliver data products useful to the organization business.

The process of converting large amounts of unstructured raw data, retrieved from different sources to a data product useful for organizations forms the core of Big Data Analytics.

In this tutorial, we will discuss the most fundamental concepts and methods of Big Data Analytics.

Topics include :

• Big Data Analytics Tutorial
• Big Data Analytics - Home
• Big Data Analytics - Overview
• Big Data Analytics - Data Life Cycle
• Big Data Analytics - Methodology
• Core Deliverables
• Key Stakeholders
• Big Data Analytics - Data Analyst
• Big Data Analytics - Data Scientist

• Big Data Analytics Project
• Data Analytics - Problem Definition
• Big Data Analytics - Data Collection
• Big Data Analytics - Cleansing data
• Big Data Analytics - Summarizing
• Big Data Analytics - Data Exploration
• Data Visualization

• Big Data Analytics Methods
• Big Data Analytics - Introduction to R
• Data Analytics - Introduction to SQL
• Big Data Analytics - Charts & Graphs
• Big Data Analytics - Data Tools
• Data Analytics - Statistical Methods

• Advanced Methods
• Machine Learning for Data Analysis
• Naive Bayes Classifier
• K-Means Clustering
• Association Rules
• Big Data Analytics - Decision Trees
• Logistic Regression
• Big Data Analytics - Time Series
• Big Data Analytics - Text Analytics
• Big Data Analytics - Online Learning

• Big Data Analytics Useful Resources
• Big Data Analytics - Quick Guide
• Big Data Analytics - Resources
• Big Data Analytics - Discussion

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28 Examples of Artificial Intelligence Shaking Up Business as Usual

 Examples of  (AI) in pop culture usually involve a pack of intelligent robots hell-bent on overthrowing the human race, or at least a fancy theme park. Sentient machines with general artificial intelligence don't yet exist, and they likely won't exist anytime soon, so we're safe... for now. 

ARTIFICIAL INTELLIGENCE EXAMPLES

• Manufacturing robots
• Self-driving cars
• Smart assistants
• Proactive healthcare management
• Disease mapping
• Automated financial investing
• Virtual travel booking agent
• Social media monitoring
• Inter-team chat tool
• Conversational marketing bot
• Natural Language Processing (NLP) tools...

Take a deeper dive into these 28 examples of artificial intelligence showing the breadth of the technology's applications across multiple industries. 

ROBOTICS

Roboticists understand robots to be programmable machines that carry out tasks, but nobody can pinpoint exactly where that definition ends.

IROBOT: SMARTER HOME ROBOTS

The makers of the popular Roomba, iRobot, are back with a new, much smarter robotic vacuum. 

HANSON ROBOTICS: BUILDING HUMANOID ROBOTS

The Hanson-created Sophia (pictured above) is an incredibly advanced social-learning robot. Through AI, Sophia can efficiently communicate with natural language.

EOTECH: OLLY, AN AI ASSISTANT WITH A PERSONALITY

the creator of Olly a voice-controlled AI assistant similar to Amazon Alexa or Google Home, but with one distinct different personality.

  Healthcare 

Artificial intelligence is proving to be a game-changer in healthcare, improving virtually every aspect of the industry from robot-assisted surgeries to safeguarding private records against cybercriminals.

COVERA  HEALTH

The company’s proprietary technology utilizes a framework that combines advanced data science and artificial intelligence to sort through existing diagnostics to provide practitioners

PATHAI: IMPROVING DIAGNOSTIC PATHOLOGY

The company's machine learning algorithms help pathologists analyze tissue samples and make more accurate diagnoses. The aim is to not only improve diagnostic accuracy, but also treatment. PathAI's technology can also identify optimal clinical trial participants.

PAGER: PROACTIVE HEALTHCARE MANAGEMENT

The company deploys machine learning to analyze clinical and claims data to discover gaps in a patient’s healthcare treatment. In addition to making healthcare recommendations.

ATOMWISE: STREAMLINING DRUG DISCOVERY

The company’s AI has improved hit rates by 10,000x and screens 10 to 20 million compounds a day while identifying characteristics of patients for clinical trials. With the ability to analyze billions of compounds and identify areas for drug discovery, the technology is rapidly speeding up the work of chemists.

MASSACHUSETTS GENERAL HOSPITAL: AI IN THE ER AND BEYOND

The programs are currently training with more than 10 billion medical images in radiology and pathology to facilitate faster testing and diagnostic capabilities.

SELF DRIVING CARS

Self-driving cars are the ultimate sign that the future is upon us. Once considered science fiction, self-driving technology is slowly inching its way towards a driverless reality. 

CRUISE: SELF-DRIVING INTO THE FUTURE

AI uses this massive data set to constantly learn about the best safety measures, driving techniques, most efficient routes, etc. to give the rider the ultimate assurance that they are safe.

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How Three Artificial Intelligence Technologies Can Sharpen a Company’s Strategic Edge

 Using Artificial Intelligence, corporations can see new patterns in their data and maintain a competitive edge. Blending these AI technologies into business strategy and operations is the subject of a newly published book.

Deploying Artificial Intelligence (AI) in a corporate business can be a costly endeavor. The payback period may be slightly longer. But longer-term, the benefits of implementing these technologies would by far exceed the initial investment, says Prof Tankiso Moloi. 

Getting ready for AI

“Artificial Intelligence technology makes machines intelligent. In some applications AIs are more intelligent than human beings,” says Prof Tshilidzi Marwala.  
Marwala is a globally recognized researcher in Artificial Intelligence at the University of Johannesburg. He is the author of a series of books.

“Many AI’s are now used in industry. For example, technologies producing goods and services, or working in call centers. Some call this the ‘industrialization of decision-making’,” he says.

“Because of this, the very nature of a firm is changing. The very nature of markets is changing as well. AI technology makes markets much more efficient. Also, suppliers and customers have more similar information. For these reasons, AI’s impact on the industry will keep on increasing,”

Why AI can supercharge fraud detection

Detecting fraud is a classic example of sooner is better, and where AI can make a big difference, says Moloi.

Let’s say you’re in a corporate business and some transactions don’t pass the smell test. You may have to wait quite long for a traditional internal control system/internal audit to take place and uncover that fraud.

When the auditors arrive, they sample the financial records. Usually, there isn’t enough capacity to look at all the records, so they take a scientific sample, and base the audit on that. The thing is, the sample may or may not contain the traces of fraud to be successfully recognized as a

fraud.

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Tutorial : JAVA T POINT

Today we are introduced to a tutorial about the following topics

let's go

1 . Machine Learning

Machine Learning tutorial provides basic and advanced concepts of machine learning. Our machine learning tutorial is designed for students and working professionals.

Machine learning is a growing technology that enables computers to learn automatically from past data. Machine learning uses various algorithms for building mathematical models and making predictions using historical data or information. Currently, it is being used for various tasks such as image recognition, speech recognition, email filtering, Facebook auto-tagging, recommender system, and many more.

2.DBMS

DBMS Tutorial provides basic and advanced concepts of Databases. Our DBMS Tutorial is designed for beginners and professionals.

The database management system is software that is used to manage the database. Our DBMS Tutorial includes all topics of DBMS such as introduction, ER model, keys, relational model, join operation, SQL, functional dependency, transaction, concurrency control, etc.

3. Java

Our core Java programming tutorial is designed for students and working professionals. Java is an object-oriented, class-based, concurrent, secured, and general-purpose computer programming language. It is a widely used robust technology.

4. Blockchain

Blockchain Tutorial provides basic and advanced concepts of blockchain. Blockchain is a constantly growing ledger that keeps a permanent record of all the transactions that have taken place in a secure, chronological, and immutable way. It can be used for the secure transfer of money, property, contracts, etc. without requiring a third-party intermediary such as a bank or government. Blockchain is a software protocol, but it could not be run without the Internet (like SMTP is for email).

5. Control Systems

Control Systems Tutorial provides basic and advanced concepts of Control System Library. Our Control System Tutorial is designed for beginners and professionals. Our Control System Tutorial includes all topics of Control System Tutorial such as Control System Introduction, Classification, Transfer Function, Signal flow graphs, Mason gain formula, Block diagram, State Space Model, etc.

6. Selenium

Selenium tutorial provides basic and advanced concepts of Selenium. Our Selenium tutorial is designed for beginners and professionals. Selenium is one of the most widely used open-source Web UI (User Interface) automation testing suites. Our Selenium tutorial includes all topics of Selenium such as Features, Selenium vs QTP, Selenium Tool Suits, Selenium IDE, Selenium IDE Locating Strategies, Selenium WebDriver, WebDriver Features, WebDriver vs RC, WebDriver Installation, etc.

7.

HTML 5 tutorial provides basic and advanced concepts of HTML. Our HTML tutorial is developed for beginners and professionals. In our tutorial, every topic is given step-by-step so that you can learn it in a very easy way. If you are new to learning HTML, then you can learn HTML from a basic to a professional level and after learning HTML with CSS and JavaScript you will be able to create your own interactive and dynamic website. But Now We will focus on HTML only in this tutorial.

8. CSS

CSS tutorial or CSS 3 tutorial provides basic and advanced concepts of CSS technology. Our CSS tutorial is developed for beginners and professionals. The major points of CSS are given below:

• CSS stands for Cascading Style Sheet.
• CSS is used to design HTML tags.
• CSS is a widely used language on the web.
• HTML, CSS, and JavaScript are used for web designing. It helps web designers to apply style on HTML tags.

9. JavaScript 

JavaScript Tutorial is designed for both beginners and professionals. JavaScript is used to create client-side dynamic pages.JavaScript is an object-based scripting language that is lightweight and cross-platform.JavaScript is not a compiled language, but it is a translated language. The JavaScript Translator (embedded in the browser) is responsible for translating the JavaScript code for the web browser.

10. Data Structures 

Data Structures (DS) tutorial provides basic and advanced concepts of Data Structure. Our Data Structure tutorial is designed for beginners and professionals.

Data Structure is a way to store and organize data so that it can be used efficiently.

Our Data Structure tutorial includes all topics of Data Structure such as Array, Pointer, Structure, Linked List, Stack, Queue, Graph, Searching, Sorting, Programs, etc.

11. jQuery

jQuery tutorial for beginners and professionals provides deep knowledge of jQuery technology. Our jQuery tutorial will help you to learn jQuery fundamentals, for example, selectors, events, effects, traversing, CSS and attributes.

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