Supervised Machine Learning: All You Need to Know | Simplilearn
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Supervised Machine Learning: All You Need to Know | Simplilearn
This article provides an overview of supervised learning core components. Before going deep into supervised learning, let’s take a short tour of What is machine learning.
7 months ago
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Main Challenges in Machine Learning: 1. Insufficient or Poor-Quality Data Lack of labeled data for supervised learning. Noisy, incomplete, or biased data can lead to poor models. 2. Overfitting and Underfitting Overfitting: Model performs well on training data but poorly on new data. Underfitting: Model is too simple to capture the underlying pattern. 3. High Computational Cost Training complex models (e.g., deep learning) requires powerful hardware and GPUs. 4. Scalability Models trained on sma
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🎯 الفرق بين Supervised وUnsupervised وReinforcement Learning في تعلم الآلة ✨ تعلم الآلة (Machine Learning) هو الأساس الذي يُبنى عليه الذكاء الاصطناعي الحديث، وينقسم إلى 3 أنواع رئيسية، كل نوع له طريقته في "التعلم" من البيانات👇 --- 🔹 1️⃣ Supervised Learning (التعلم الموجّه) النموذج يتعلّم من بيانات معلّمة (مدخلات نتائج صحيحة). يُستخدم في: 🔸 Classification: مثل تصنيف البريد الإلكتروني Spam / Not Spam 🔸 Regression: مثل التنبؤ بأسعار العقارات 🧠 من أشهر الخوارزميات: Logistic Regression – Random
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