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@booksbylisaa: Vous pouvez m’oublier #bookgirl #BookTok #humour

Lisa 🫧
Lisa 🫧
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Wednesday 07 October 2026 10:32:27 GMT
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बुधबार बिहान लियोन मेसीले अन्तिम अन्तर्राष्ट्रिय खेल खेले, बेनिनविरुद्ध। अर्जेन्टिनाको जर्सीमा मेसीले लेखेको अन्तिम खेल हेर्न हजारौं दर्शक मैदानमा आएका थिए भने लाखौं समर्थक चोक, सडक, गल्ली र घरमै लाइभ हेरिरहेका छन्। खेलमा मेसीले १ गोल २ असिस्ट गरेपछि अर्जेन्टिना ३–०ले विजयी भयो। खेलमा रेफ्रिको भूमिका थिए, चिलीका फर्नान्डो भेहार। जब उनले खेलसकिएको सिठी बजाए, मेसी हात मिलाउन उनिभएतिर आए। त्यसपछि भेहारले गोजीबाट पहेँलो र रातो दुवै कार्ड निकाले, अनि मेसीलाई दुवै कार्ड दिँदै उनीप्रति सम्मान व्यक्त गरे। #messi #messifans #MessiMagic
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Let’s use Machine Learning to predict whether a student will get placed based on their academic & skill data! 🚀 📌 Goal: Build a model that predicts placement status using student information like: • 🎯 CGPA / Grades • 💬 Communication Skills • 🏆 Internship Experience • 💻 Technical Skills • 📜 Certifications 🛠 Steps to Build: 1️⃣ Data Collection → Gather past student placement records. 2️⃣ Data Preprocessing → Handle missing values, encode categories. 3️⃣ EDA (Exploratory Data Analysis) → Find trends (e.g., CGPA vs Placement). 4️⃣ Model Selection → Try Logistic Regression, Decision Trees, Random Forests. 5️⃣ Training & Testing → Split into train/test sets. 6️⃣ Evaluation → Check accuracy, precision, recall. 7️⃣ Deployment → Use Streamlit / Flask for a web app. 💡 Insights You Can Find: • 📈 Higher CGPA increases placement chances. • 🧠 Soft skills matter more than we think! • 🖥 Certain technical skills boost job prospects. ⚡ Tools You Can Use: • Python 🐍 • Pandas & NumPy 📊 • Scikit-learn 🤖 • Matplotlib / Seaborn 🎨 💬 From data to decisions — let’s make student futures brighter with ML! 🌟 #MachineLearning #DataScience #StudentPlacement #CareerSuccess #Day12 #MLProjects #AIInEducation
Let’s use Machine Learning to predict whether a student will get placed based on their academic & skill data! 🚀 📌 Goal: Build a model that predicts placement status using student information like: • 🎯 CGPA / Grades • 💬 Communication Skills • 🏆 Internship Experience • 💻 Technical Skills • 📜 Certifications 🛠 Steps to Build: 1️⃣ Data Collection → Gather past student placement records. 2️⃣ Data Preprocessing → Handle missing values, encode categories. 3️⃣ EDA (Exploratory Data Analysis) → Find trends (e.g., CGPA vs Placement). 4️⃣ Model Selection → Try Logistic Regression, Decision Trees, Random Forests. 5️⃣ Training & Testing → Split into train/test sets. 6️⃣ Evaluation → Check accuracy, precision, recall. 7️⃣ Deployment → Use Streamlit / Flask for a web app. 💡 Insights You Can Find: • 📈 Higher CGPA increases placement chances. • 🧠 Soft skills matter more than we think! • 🖥 Certain technical skills boost job prospects. ⚡ Tools You Can Use: • Python 🐍 • Pandas & NumPy 📊 • Scikit-learn 🤖 • Matplotlib / Seaborn 🎨 💬 From data to decisions — let’s make student futures brighter with ML! 🌟 #MachineLearning #DataScience #StudentPlacement #CareerSuccess #Day12 #MLProjects #AIInEducation

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