Car Price Prediction with Linear Regression Model

What’s the biggest dataset you’ve ever scraped? Curious about this. A lot of scraping discussions focus on techniques, but not much on scale. What’s the largest dataset you’ve personally collected from scraping? Thousands of pages? Millions? Also curious what problems started appearing once things got bigger. #WebScraping #BigData #DataEngineering #Python #DataScience #WebData

This problem demonstrates how dictionary comprehensions can create key–value pairs dynamically. It highlights how values can be generated from existing data while building a dictionary in a compact and readable way. A very useful technique when transforming datasets. THE ANSWER IS: B #Python #DictionaryComprehension #PythonChallenge #DataStructures #BuildInPublic

During this workshop, I learned: •Creating interactive visualizations in Python •Debugging Python code efficiently using AI •Writing optimized Python code with AI assistance This experience enhanced my practical understanding of Python and AI-driven development. Looking forward to applying these skills in real-world projects through AI for Techies #Python #ArtificialIntelligence #AI #Workshop #Learning

Applying ANOVA analysis in Python 📊 Used Statsmodels and Pandas to examine whether Total Liabilities significantly differ based on TAD (Total Asset Dummy) in the financial dataset. Learning how statistical techniques help uncover meaningful financial insights. #Python #DataAnalytics #ANOVA #FinancialAnalysis #LearningByDoing 🚀

Mastering machine learning sounds cool until you're buried in math, lost in algorithms, and wondering what Python package you're supposed to install next. If you've ever: - Opened a tutorial and closed it 10 minutes later - Felt like everyone else already gets it - Wondered where you were supposed to start... This blog post can help you. It breaks down the real path to getting started with machine learning using Python. #MachineLearning #Python #AI #DataScience #RheinwerkComputingBlog #RheinwerkComputingInfographic Take your first (or next) step here: https://hubs.la/Q0448D_q0

I tried bootstrapping the data before and after cleaning and compared it with the data after using Python to create a machine learning model. There was a change in the standard deviation and a narrowing of the P10 and P90 values. Data source: Alysa Suydam #python #datascience #machinelearning #geoscientist #geoscience #tds 

🚀 Excited to share my project — Industrial Human Resource Geo-Visualization Dashboard built using Python, Pandas, Scikit-learn, Plotly and Streamlit! GitHub: https://lnkd.in/g8NXc7uG #Python #DataScience #Streamlit #GUVI #MachineLearning

I picked up Python this week. Learning AI is one of the key skills I plan to add to my portfolio, and Python sits right at the foundation of that journey. Yes, there are plenty of documentation tools out there. But I want to build custom automation tools that work specifically for the products I document. I plan to combine Python fundamentals with AI to build smarter, more intentional tools for documentation. #TechnicalWriting #Python #AI #Documentation #LearningInPublic

SkillCourse Day 5/30: Mastering User Interaction in Python I just wrapped up Day 5 of the "30 Days of Python with AI" challenge by Satish Dhawale sir! Today was all about making programs interactive. Key takeaways: The input() function: Learning how to capture user data. Type Casting: Why converting strings to int() or float() is crucial for calculations (no more 1 + 1 = 11 errors!). Data Integrity: Understanding how Python handles different data types during input. #Python #CodingChallenge #AI #LearningInPublic #SatishDhawale #DataAnalyst