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SQL Interview Success: Unlocking the Top 5 Frequently Asked Queries

 Here are the five top commonly asked SQL queries in the interviews. These you can expect in Data Analyst, or, Data Engineer interviews. Top SQL Queries for Interviews 01. Joins The commonly asked question pertains to providing two tables, determining the number of rows that will return on various join types, and the resultant. Table1 -------- id ---- 1 1 2 3 Table2 -------- id ---- 1 3 1 NULL Output ------- Inner join --------------- 5 rows will return The result will be: =============== 1  1 1   1 1   1 1    1 3    3 02. Substring and Concat Here, we need to write an SQL query to make the upper case of the first letter and the small case of the remaining letter. Table1 ------ ename ===== raJu venKat kRIshna Solution: ========== SELECT CONCAT(UPPER(SUBSTRING(name, 1, 1)), LOWER(SUBSTRING(name, 2))) AS capitalized_name FROM Table1; 03. Case statement SQL Query ========= SELECT Code1, Code2,      CASE         WHEN Code1 = 'A' AND Code2 = 'AA' THEN "A" | "A

Quick Guide: Machine Learning Examples and Uses

Machine learning

I want to share with you the best real-time examples on machine learning. Because of new computing technologies, machine learning today is not like machine learning of the past. 

While many machine learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data – over and over, faster and faster – is a recent development.

Machine learning use cases
  • The heavily hyped, self-driving Google car? The essence of machine learning. 
  • Online recommendation offers like those from Amazon and Netflix? Machine learning applications for everyday life. 
  • Knowing what customers are saying about you on Twitter? Machine learning combined with linguistic rule creation. 
  • Fraud detection? One of the more obvious, important uses in our world today.
Best example: "pattern recognition" is best example for Machine Learning
Where can you apply machine learning. The following are the key areas you can apply machine learning.
  1. Fraud detection.
  2. Web search results.
  3. Real-time ads on web pages and mobile devices.
  4. Text-based sentiment analysis.
  5. Credit scoring and next-best offers.
  6. Prediction of equipment failures.
  7. New pricing models.
  8. Network intrusion detection.
  9. Pattern and image recognition.
  10. Email spam filtering.


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