3( 1) Challenges in Personalized Learning
3( 1) Challenges in Personalized Learning
Jun 23, 2016
patch.com
Caregiving isn't always easy; there are tough days and moments of frustration. Remembering who the person was before illness can offer valuable perspective. It's okay to struggle with temper and difficult situations, especially when routines change. Have you ever felt this? #caregiver #patience #perspective #challenges #support | I'm Betty
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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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