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Update pages/100_Graduate_Machine_Learning.py
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pages/100_Graduate_Machine_Learning.py
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5. Explore fairness in machine learning using real-world datasets.
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""")
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# Assessments Section
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st.header("Assessments")
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st.write("""
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- **Midterm Project**: Design and implement a machine learning model that incorporates advanced theoretical methods and optimization techniques.
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- **Final Research Paper**: Write and present a research paper on a selected topic in advanced machine learning
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5. Explore fairness in machine learning using real-world datasets.
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""")
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# Assessments Section (continued)
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st.write("""
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- **Midterm Project**: Design and implement a machine learning model that incorporates advanced theoretical methods and optimization techniques.
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- **Final Research Paper**: Write and present a research paper on a selected topic in advanced machine learning, proposing a novel method, or experimenting with cutting-edge models.
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""")
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# Additional Resources Section
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st.header("Additional Resources")
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st.write("""
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- **Books**:
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- "Elements of Statistical Learning" by Hastie, Tibshirani, Friedman
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- "Pattern Recognition and Machine Learning" by Christopher M. Bishop
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- "Deep Learning" by Ian Goodfellow, Yoshua Bengio, Aaron Courville
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- "Reinforcement Learning: An Introduction" by Richard S. Sutton and Andrew G. Barto
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- "The Book of Why" by Judea Pearl (for causal inference)
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- **Libraries & Tools**:
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- **PyTorch**: A deep learning framework used for various implementations (GANs, VAEs, etc.).
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- **TensorFlow**: Another widely-used deep learning library.
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- **Hugging Face**: Pre-trained models for transfer learning and NLP tasks.
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- **OpenAI Gym**: A toolkit for developing and comparing reinforcement learning algorithms.
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- **Pyro**: A probabilistic programming library built on PyTorch for Bayesian networks and probabilistic models.
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- **Research Journals & Conferences**:
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- NeurIPS (Neural Information Processing Systems)
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- ICML (International Conference on Machine Learning)
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- ICLR (International Conference on Learning Representations)
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""")
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# Footer Section
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st.write("Good luck with your studies and projects in advanced machine learning! Stay curious and keep exploring.")
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# End of Streamlit App
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