Data Science & Machine Learning
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Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free

For collaborations: @love_data
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๐Ÿ“Š Data Science Project Ideas to Practice & Master Your Skills โœ…

๐ŸŸข Beginner Level
โ€ข Titanic Survival Prediction (Logistic Regression)
โ€ข House Price Prediction (Linear Regression)
โ€ข Exploratory Data Analysis on IPL or Netflix Dataset
โ€ข Customer Segmentation (K-Means Clustering)
โ€ข Weather Data Visualization

๐ŸŸก Intermediate Level
โ€ข Sentiment Analysis on Tweets
โ€ข Credit Card Fraud Detection
โ€ข Time Series Forecasting (Stock or Sales Data)
โ€ข Image Classification using CNN (Fashion MNIST)
โ€ข Recommendation System for Movies/Products

๐Ÿ”ด Advanced Level
โ€ข End-to-End Machine Learning Pipeline with Deployment
โ€ข NLP Chatbot using Transformers
โ€ข Real-Time Dashboard with Streamlit + ML
โ€ข Anomaly Detection in Network Traffic
โ€ข A/B Testing & Business Decision Modeling

๐Ÿ’ฌ Double Tap โค๏ธ for more! ๐Ÿค–๐Ÿ“ˆ
โค6
Guys, Big Announcement!

Weโ€™ve officially hit 2.5 Million followers โ€” and itโ€™s time to level up together! โค๏ธ

Iโ€™m launching a Python Projects Series โ€” designed for beginners to those preparing for technical interviews or building real-world projects.

This will be a step-by-step, hands-on journey โ€” where youโ€™ll build useful Python projects with clear code, explanations, and mini-quizzes!

Hereโ€™s what weโ€™ll cover:

๐Ÿ”น Week 1: Python Mini Projects (Daily Practice)
โฆ Calculator
โฆ To-Do List (CLI)
โฆ Number Guessing Game
โฆ Unit Converter
โฆ Digital Clock

๐Ÿ”น Week 2: Data Handling & APIs
โฆ Read/Write CSV & Excel files
โฆ JSON parsing
โฆ API Calls using Requests
โฆ Weather App using OpenWeather API
โฆ Currency Converter using Real-time API

๐Ÿ”น Week 3: Automation with Python
โฆ File Organizer Script
โฆ Email Sender
โฆ WhatsApp Automation
โฆ PDF Merger
โฆ Excel Report Generator

๐Ÿ”น Week 4: Data Analysis with Pandas & Matplotlib
โฆ Load & Clean CSV
โฆ Data Aggregation
โฆ Data Visualization
โฆ Trend Analysis
โฆ Dashboard Basics

๐Ÿ”น Week 5: AI & ML Projects (Beginner Friendly)
โฆ Predict House Prices
โฆ Email Spam Classifier
โฆ Sentiment Analysis
โฆ Image Classification (Intro)
โฆ Basic Chatbot

๐Ÿ“Œ Each project includes: 
โœ… Problem Statement 
โœ… Code with explanation 
โœ… Sample input/output 
โœ… Learning outcome 
โœ… Mini quiz

๐Ÿ’ฌ React โค๏ธ if you're ready to build some projects together!

You can access it for free here
๐Ÿ‘‡๐Ÿ‘‡
https://whatsapp.com/channel/0029VaiM08SDuMRaGKd9Wv0L

Letโ€™s Build. Letโ€™s Grow. ๐Ÿ’ป๐Ÿ™Œ
โค13๐Ÿ‘1
๐Ÿ’ ๐…๐ซ๐ž๐ž ๐ƒ๐’๐€ ๐‘๐ž๐ฌ๐จ๐ฎ๐ซ๐œ๐ž๐ฌ ๐ญ๐จ ๐‚๐ซ๐š๐œ๐ค ๐‚๐จ๐๐ข๐ง๐  ๐ˆ๐ง๐ญ๐ž๐ซ๐ฏ๐ข๐ž๐ฐ๐ฌ๐Ÿ˜

Cracking coding interviews isnโ€™t about luckโ€”itโ€™s about mastering Data Structures and Algorithms (DSA) with the right resources๐Ÿ–ฅ๐ŸŽ–

Whether youโ€™re aiming for FAANG, top MNCs, or fast-growing startups, having a strong foundation in DSA will set you apart๐Ÿง‘โ€๐ŸŽ“๐Ÿ’ฅ

๐‹๐ข๐ง๐ค๐Ÿ‘‡:-

https://pdlink.in/41MsPpe

Start today and turn your DSA fear into DSA mastery!โœ…๏ธ
โค1
Which of the following is essential for any well-documented data science project?
Anonymous Quiz
5%
a) Fancy UI design
3%
b) Only code files
83%
c) README file explaining problem, steps & results
10%
d) Just a model accuracy score
โค2
Your model performs well on training data but poorly on test data. Whatโ€™s likely missing?
Anonymous Quiz
25%
a) Hyperparameter tuning
69%
b) Overfitting handling
3%
c) More print statements
3%
d) Fancy visualizations
โค1
Which file should you upload along with your Jupyter Notebook to make your project reproducible?
Anonymous Quiz
6%
a) Screenshot of results
12%
b) Excel output file
76%
c) requirements.txt or environment.yml
6%
d) A video walkthrough
โค1
โค1
Which of the following is NOT a recommended practice when uploading a data science project to GitHub?*
Anonymous Quiz
20%
A) Including a well-written README.md with setup and usage instructions
66%
B) Uploading large raw datasets directly into the repository
8%
C) Organizing code into modular scripts under a src/ folder
7%
D) Providing a requirements.txt or environment.yml for dependencies
โค1
๐—•๐—ฒ๐—ฐ๐—ผ๐—บ๐—ฒ ๐—ฎ ๐—–๐—ฒ๐—ฟ๐˜๐—ถ๐—ณ๐—ถ๐—ฒ๐—ฑ ๐——๐—ฎ๐˜๐—ฎ ๐—”๐—ป๐—ฎ๐—น๐˜†๐˜€๐˜ ๐—œ๐—ป ๐—ง๐—ผ๐—ฝ ๐— ๐—ก๐—–๐˜€๐Ÿ˜

Learn Data Analytics, Data Science & AI From Top Data Experts 

Curriculum designed and taught by Alumni from IITs & Leading Tech Companies.

๐—›๐—ถ๐—ด๐—ต๐—น๐—ถ๐—ด๐—ต๐˜๐—ฒ๐˜€:- 
- 12.65 Lakhs Highest Salary
- 500+ Partner Companies
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๐—•๐—ผ๐—ผ๐—ธ ๐—ฎ ๐—™๐—ฅ๐—˜๐—˜ ๐——๐—ฒ๐—บ๐—ผ๐Ÿ‘‡:-

๐—ข๐—ป๐—น๐—ถ๐—ป๐—ฒ :- https://pdlink.in/4fdWxJB

๐—›๐˜†๐—ฑ๐—ฒ๐—ฟ๐—ฎ๐—ฏ๐—ฎ๐—ฑ :- https://pdlink.in/4kFhjn3

๐—ฃ๐˜‚๐—ป๐—ฒ :- https://pdlink.in/45p4GrC

( Hurry Up ๐Ÿƒโ€โ™‚๏ธLimited Slots )
โค3
๐— ๐—ผ๐˜€๐˜ ๐—”๐˜€๐—ธ๐—ฒ๐—ฑ ๐—ฆ๐—ค๐—Ÿ ๐—œ๐—ป๐˜๐—ฒ๐—ฟ๐˜ƒ๐—ถ๐—ฒ๐˜„ ๐—ค๐˜‚๐—ฒ๐˜€๐˜๐—ถ๐—ผ๐—ป๐˜€ ๐—ฎ๐˜ ๐— ๐—”๐—”๐—ก๐—š ๐—–๐—ผ๐—บ๐—ฝ๐—ฎ๐—ป๐—ถ๐—ฒ๐˜€๐Ÿ”ฅ๐Ÿ”ฅ

1. How do you retrieve all columns from a table?

SELECT * FROM table_name;


2. What SQL statement is used to filter records?

SELECT * FROM table_name
WHERE condition;

The WHERE clause is used to filter records based on a specified condition.


3. How can you join multiple tables? Describe different types of JOINs.

SELECT columns
FROM table1
JOIN table2 ON table1.column = table2.column
JOIN table3 ON table2.column = table3.column;

Types of JOINs:

1. INNER JOIN: Returns records with matching values in both tables

SELECT * FROM table1
INNER JOIN table2 ON table1.column = table2.column;

2. LEFT JOIN (or LEFT OUTER JOIN): Returns all records from the left table and matched records from the right table. Unmatched records will have NULL values.

SELECT * FROM table1
LEFT JOIN table2 ON table1.column = table2.column;

3. RIGHT JOIN (or RIGHT OUTER JOIN): Returns all records from the right table and matched records from the left table. Unmatched records will have NULL values.

SELECT * FROM table1
RIGHT JOIN table2 ON table1.column = table2.column;

4. FULL JOIN (or FULL OUTER JOIN): Returns records when there is a match in either left or right table. Unmatched records will have NULL values.

SELECT * FROM table1
FULL JOIN table2 ON table1.column = table2.column;


4. What is the difference between WHERE and HAVING clauses?

WHERE: Filters records before any groupings are made.

SELECT * FROM table_name
WHERE condition;

HAVING: Filters records after groupings are made.

SELECT column, COUNT(*)
FROM table_name
GROUP BY column
HAVING COUNT(*) > value;


5. How do you count the number of records in a table?

SELECT COUNT(*) FROM table_name;

This query counts all the records in the specified table.

6. How do you calculate average, sum, minimum, and maximum values in a column?

Average: SELECT AVG(column_name) FROM table_name;

Sum: SELECT SUM(column_name) FROM table_name;

Minimum: SELECT MIN(column_name) FROM table_name;

Maximum: SELECT MAX(column_name) FROM table_name;


7. What is a subquery, and how do you use it?

Subquery: A query nested inside another query

SELECT * FROM table_name
WHERE column_name = (SELECT column_name FROM another_table WHERE condition);




Till then keep learning and keep exploring ๐Ÿ™Œ
โค5๐Ÿ‘2