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HOW DOES NETFLIX KNOW WHAT YOU'LL WATCH NEXT?

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  Every time Netflix recommends a show you end up loving, every time an e-commerce site predicts how much stock to order, every time a bank decides whether to approve your loan , there's a good chance regression is working quietly in the background. Regression analysis is one of the most widely used tools in data analytics. And yet most people outside the data world have never heard of it. In this blog, I'm going to change that — no formulas, no textbook definitions, just real business examples that show you exactly what regression does and why companies can't live without it. SO WHAT EXACTLY IS REGRESSION ? Think of regression as a tool that answers one very specific question: "If I change X, what happens to Y?" For example: - If I increase my ad spend by ₹10,000, how much will my sales go up? - If a house has one more bedroom, how much more will it sell for? - If a customer has been with us for 2 more years, how likely are they to churn? Regression finds the m...

WHAT ACTUALLY DRIVES SALES INSIDE A BLINKIT DARK STORE?| I ANALYZED 8,500+ RECORDS TO FIND OUT.

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Quick commerce is a ₹5 billion industry built on a simple promise  your groceries in 10 minutes. But inside those dark stores, what actually determines whether one outlet earns ₹500 per product or ₹2,400? I spent weeks analyzing 8,523 Blinkit sales records using Python to find out. Some answers were expected. Others genuinely surprised me. THE PROJECT -WHAT I WAS TRYING TO ANSWER For my project , I picked a dataset that felt real  Blinkit's product-outlet sales records.  It had 8,523 rows and 12 variables: product type, weight, MRP, fat content, outlet size, location tier, outlet format, and more.  The target variable was Item Outlet Sales, the revenue each product generated at each outlet. My goal was simple but important: figure out which factors actually drive sales performance. And then build a regression model to predict it. Quick numbers: - 8,523 sales records analyzed - 12 variables in the dataset - ₹1,499 average item outlet sales - 16 product categories STEP...

PYTHON - OOP(OBJECT ORIENTED PROGRAMMING) - PART 1

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  OOP IN PYTHON --  To map with real world scenarios, we started using objects in code. This is called Object Oriented Programming. -- Utilizing functions reduces redundancy and enhances code reusability.  CLASS AND OBJECT IN PYTHON -- Class is a blueprint which tells us that what features should a class have. -- All the information which we have to store in particular object and writing in a class is what we call blueprint for creating an object # First we have to define class   * Creating class   class Student:                (Remember you always have to start class's name by capital letter)         name = "Anshula"     * After creating class, we need to create object Eg: s1 = Student () print(s1.name)     (object and instances of class is same) ** Suppose there is a factory and you are required to create a class. class Car:     color = "blue"     bran...

LEARNING DATA SCIENCE , PART 3

 DATA TYPES IN PYTHON   1. NUMBERS - Integers i.e whole numbers , not decimal 2. FLOAT Floats are the decimal numbers . Example - 4.3 , 5.7  3. Complex Number  x + iy  , here x = real number and y = imaginery 4. Boolean Boolean is either true or false  5. SET  Set is a collection of data Set only contains unique elements , repititions are not allowed. 6. DICTIONARY  It states in the from of key and it's value terms. {name : 'John , Age:'25' , 'city':25 , 'New year'} 7. STRING It is the most commonly used data type. Write in between of commas "   ". 8. LIST  List is collection of items and it can have duplicate items. my_list = [1,2,3,4,5] 9. TUPLES  Tuples are immutable ( means we can not modify the code once written). 10. NONE   When the type of data does not exist that is known as NONE . Now, we will move forward to PYTHON OPERATORS  1. ARITHMETIC OPERATORS #ADDITION (+)  a + b (operand), here a = ope...

LEARNING DATA SCIENCE , WEEK 2

 PYTHON KEYWORDS Python keywords are special reserved words that have specific meanings and purposes and can not be used for anything but those specific purposes. Note: There is a function in python ,when you execute that it will show the list of python keywords. FUNCTION - help('keywords') PYTHON IDENTIFIERS Variable - Anything which holds certain value. The identifier is used to identify an entirely unique in a program at the time of execution. Example - name = 'ANSHULA' name is representing unique identity ANSHULA . There are few rules to define identifiers. 1. Use only alphabets , numbers or underscore. 2. Use of Special characters and keywords is not allowed. 3. Starting characters should be either underscore or alphabets , numbers are not allowed. COMMENT IN PYTHON  Comment is additonal information about the code you have written so that other developer can understand that code, in case he wants to reprogram that code. # - Using this means you are writting a comme...

LEARNING DATA SCIENCE , WEEK 1

  INTRODUCTION TO PROGRAMMING   -WHAT IS PROGRAMMING? There should be a common language so that both human and computer can understand. Programming language is a way to communicate with computer ,humans understands programming and write a code, then computer execute it to follow instructions. PROCEDURAL PROGRAMMING This programming was introduced in 1980s. It is a form of programming in which problem solving involves breaking down the task into sequential steps , with a boolean decision made at each step. Example - C language. To address real life issues it is essential to convert real entities in world of programming. OBJECT - it represents real entities , the object has it's own state and behaviour. RELATIONSHIP - object oriented principles (OOP) represents relationships. PYTHON CONTAINS - 1. Procedural  2. OOP 3. Functional  This is the reason python holds a distinctive positions for mastering data science.

HOW TO USE SQL?

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WHY USE SQL (STRUCTURED QUERY LANGUAGE)? While Excel can only handle data containing up to one million row, businesses today generate data in the billions and trillions.To manage such vast amounts of data, databases and indespensable. NOW, HOW TO CREATE TABLES IN SQL? In SQL, we utilize the CREATE command to create tables.. SYNTAX :  CREATE TABLE   "TABLE NAME"( "COLUMN 1"   "data type for column 1" "COLUMN 2"  " data type for column 2" , "COLUMN N"   'data type for column n", [table constraint]); CONSTRAINTS: 1. NOT NULL : Column cannot have null values  2. DEFAULT : Provides a default value. 3. UNIQUE : All values in column are different. 4. CHECK : Makes sure that all values. 5. PRIMARY KEY : It is use to uniquely identify a row in the table. 6.FOREIGN KEY : It is use to ensure referential integreting of data. INSERT COMMAND The INSERT INTO statement is used to add new records into a database table. SYNTAX: --- Sin...