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Important Machine Learning Algorithms 👆

𝟱 𝗙𝗿𝗲𝗲 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 𝗧𝗵𝗮𝘁’𝗹𝗹 𝗠𝗮𝗸𝗲 𝗦𝗤𝗟 𝗙𝗶𝗻𝗮𝗹𝗹𝘆 𝗖𝗹𝗶𝗰𝗸.😍 SQL seems tough, right? 😩 These 5 FREE SQL resources will take you from beginner to advanced without boring theory dumps or confusion.📊 𝐋𝐢𝐧𝐤👇:- https://pdlink.in/3GtntaC Master it with ease. 💡

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🚀 𝗛𝗼𝘄 𝘁𝗼 𝗕𝘂𝗶𝗹𝗱 𝗮 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 𝗧𝗵𝗮𝘁 𝗧𝗿𝘂𝗹𝘆 𝗦𝘁𝗮𝗻𝗱𝘀 𝗢𝘂𝘁 In today’s competitive landscape, a strong resume alone won't get you far. If you're aiming for 𝘆𝗼𝘂𝗿 𝗱𝗿𝗲𝗮𝗺 𝗱𝗮𝘁𝗮 𝘀𝗰𝗶𝗲𝗻𝗰𝗲 𝗿𝗼𝗹𝗲, you need a portfolio that speaks volumes—one that highlights your skills, thinking process, and real-world impact. A great portfolio isn’t just a collection of projects. It’s your story as a data scientist—and here’s how to make it unforgettable: 🔹 𝗪𝗵𝗮𝘁 𝗠𝗮𝗸𝗲𝘀 𝗮𝗻 𝗘𝘅𝗰𝗲𝗽𝘁𝗶𝗼𝗻𝗮𝗹 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼? ✅ Quality Over Quantity – A few impactful projects are far better than a dozen generic ones. ✅ Tell a Story – Clearly explain the problem, your approach, and key insights. Keep it engaging. ✅ Show Range – Demonstrate a variety of skills—data cleaning, visualization, analytics, modeling. ✅ Make It Relevant – Choose projects with real-world business value, not just toy Kaggle datasets. 🔥 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗜𝗱𝗲𝗮𝘀 𝗧𝗵𝗮𝘁 𝗥𝗲𝗰𝗿𝘂𝗶𝘁𝗲𝗿𝘀 𝗡𝗼𝘁𝗶𝗰𝗲 1️⃣ Customer Churn Prediction – Help businesses retain customers through insights. 2️⃣ Social Media Sentiment Analysis – Extract opinions from real-time data like tweets or reviews. 3️⃣ Supply Chain Optimization – Solve efficiency problems using operational data. 4️⃣ E-commerce Recommender System – Personalize shopping experiences with smart suggestions. 5️⃣ Interactive Dashboards – Use Power BI or Tableau to tell compelling visual stories. 📌 𝗕𝗲𝘀𝘁 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲𝘀 𝗳𝗼𝗿 𝗮 𝗞𝗶𝗹𝗹𝗲𝗿 𝗣𝗼𝗿𝘁𝗳𝗼𝗹𝗶𝗼 💡 Host on GitHub – Keep your code clean, well-structured, and documented. 💡 Write About It – Use Medium or your own site to explain your projects and decisions. 💡 Deploy Your Work – Use tools like Streamlit, Flask, or FastAPI to make your projects interactive. 💡 Open Source Contributions – It’s a great way to gain credibility and connect with others. A great data science portfolio is not just about code—it's about solving real problems with data. Free Data Science Resources: https://t.me/datalemur All the best 👍👍

Accenture Data Scientist Interview Questions! 1st round- Technical Round - 2 SQl questions based on playing around views and table, which could be solved by both subqueries and window functions. - 2 Pandas questions , testing your knowledge on filtering , concatenation , joins and merge. - 3-4 Machine Learning questions completely based on my Projects, starting from Explaining the problem statements and then discussing the roadblocks of those projects and some cross questions. 2nd round- - Couple of python questions agains on pandas and numpy and some hypothetical data. - Machine Learning projects explanations and cross questions. - Case Study and a quiz question. 3rd and Final round. HR interview Simple Scenerio Based Questions. Data Science Resources 👇👇 https://t.me/datasciencefun Like if you need similar content 😄👍

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