SortedCoding

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They waste hours on resumes, websites, and still feel stuck.

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3 hours ago | [YT] | 0

SortedCoding

*15 Best Project Ideas for Data Science*📊

🚀 *Beginner Level:*
1. Exploratory Data Analysis (EDA) on Titanic Dataset
2. Netflix Movies/TV Shows Data Analysis
3. COVID-19 Data Visualization Dashboard
4. Sales Data Analysis (CSV/Excel)
5. Student Performance Analysis

🌟 *Intermediate Level:*
6. Sentiment Analysis on Tweets
7. Customer Segmentation using K-Means
8. Credit Score Classification
9. House Price Prediction
10. Market Basket Analysis (Apriori Algorithm)

🌌 *Advanced Level:*
11. Time Series Forecasting (Stock/Weather Data)
12. Fake News Detection using NLP
13. Image Classification with CNN
14. Resume Parser using NLP
15. Customer Churn Prediction

*React ❤️ for more*

9 hours ago | [YT] | 2

SortedCoding

Which of the following is also known as Rope data structure?

1 day ago | [YT] | 5

SortedCoding

20+ Useful Python Tools

2 days ago | [YT] | 10

SortedCoding

Which of the following is the most widely used external memory data structure?

2 days ago | [YT] | 2

SortedCoding

What is the need for a circular queue?

3 days ago | [YT] | 5

SortedCoding

Which of the following data structures can be used for parentheses matching?

4 days ago | [YT] | 5

SortedCoding

*Python Detailed Roadmap* 🚀

📌 1. Basics
◼ Data Types & Variables
◼ Operators & Expressions
◼ Control Flow (if, loops)

📌 2. Functions & Modules
◼ Defining Functions
◼ Lambda Functions
◼ Importing & Creating Modules

📌 3. File Handling
◼ Reading & Writing Files
◼ Working with CSV & JSON

📌 4. Object-Oriented Programming (OOP)
◼ Classes & Objects
◼ Inheritance & Polymorphism
◼ Encapsulation

📌 5. Exception Handling
◼ Try-Except Blocks
◼ Custom Exceptions

📌 6. Advanced Python Concepts
◼ List & Dictionary Comprehensions
◼ Generators & Iterators
◼ Decorators

📌 7. Essential Libraries
◼ NumPy (Arrays & Computations)
◼ Pandas (Data Analysis)
◼ Matplotlib & Seaborn (Visualization)

📌 8. Web Development & APIs
◼ Web Scraping (BeautifulSoup, Scrapy)
◼ API Integration (Requests)
◼ Flask & Django (Backend Development)

📌 9. Automation & Scripting
◼ Automating Tasks with Python
◼ Working with Selenium & PyAutoGUI

📌 10. Data Science & Machine Learning
◼ Data Cleaning & Preprocessing
◼ Scikit-Learn (ML Algorithms)
◼ TensorFlow & PyTorch (Deep Learning)

📌 11. Projects
◼ Build Real-World Applications
◼ Showcase on GitHub

📌 12. ✅ Apply for Jobs
◼ Strengthen Resume & Portfolio
◼ Prepare for Technical Interviews

Like for more ❤️💪

4 days ago | [YT] | 7

SortedCoding

Which algorithm is used in the top tree data structure?

4 days ago | [YT] | 5

SortedCoding

*Pandas Functions for Data Analysis* 👇

Data Loading:

pd.read_csv() - Load data from a CSV file.

pd.read_excel() - Load data from an Excel file.


Data Inspection:

df.head(n) - View the first n rows.

df.info() - Get a summary of the dataset.

df.describe() - Generate summary statistics.


Data Manipulation:

df.drop(columns=['col1', 'col2']) - Remove specific columns.

df.rename(columns={'old_name': 'new_name'}) - Rename columns.

df['col'] = df['col'].apply(func) - Apply a function to a column.


Filtering and Sorting:

df[df['col'] > value] - Filter rows based on a condition.

df.sort_values(by='col', ascending=True) - Sort rows by a column.


Aggregation:

df.groupby('col').sum() - Group data and compute the sum.

df['col'].value_counts() - Count unique values in a column.


Merging and Joining:

pd.merge(df1, df2, on='key') - Merge two DataFrames.

pd.concat([df1, df2]) - Concatenate


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5 days ago | [YT] | 4