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Publicaciones del Canal
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| 7 | SKILLS WEB DEVELOPMENT SIGMA BATCH
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| 8 | +1 Python and Tkinter Programming (2000).pdf | 1 535 |
| 9 |  +3Python Most Asked Interview Questions with Answers ✅ | 1 483 |
| 10 | 100 Java Interview Questions with Answers (1).pdf | 1 160 |
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| 15 | +3 Machine Learning and AI Foundations: Causal Inference and Modeling | 1 449 |
| 16 | Understanding Bias and Variance in Machine Learning
Bias refers to the error in the model when the model is not able to capture the pattern in the data and what results is an underfit model (High Bias).
Variance refers to the error in the model, when the model is too much tailored to the training data and fails to generalise for unseen data which refers to an overfit model (High Variance)
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| 17 | Popular Python packages for data science:
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2. Pandas: For data manipulation and analysis, especially with data frames.
3. Matplotlib and Seaborn: For data visualization.
4. Scikit-learn: For machine learning algorithms and tools.
5. TensorFlow and PyTorch: Deep learning frameworks.
6. SciPy: For scientific and technical computing.
7. Statsmodels: For statistical modeling and hypothesis testing.
8. NLTK and SpaCy: Natural Language Processing libraries.
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