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" <img src=\"https://i.ibb.co/xfJbPmL/github.png\" height=\"70px\" style=\"padding-bottom:5px;\" />View Source on GitHub</a></td>\n",
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"</table>\n",
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"\n",
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"id": "rNbf1pRlSDby"
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},
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"source": [
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"# Copyright 2024 MIT 6.S191 Introduction to Deep Learning. All Rights Reserved.\n",
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"# Copyright 2025 MIT 6.S191 Introduction to Deep Learning. All Rights Reserved.\n",
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"#\n",
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"# Licensed under the MIT License. You may not use this file except in compliance\n",
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"# with the License. Use and/or modification of this code outside of 6.S191 must\n",
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"* Do you think it should be necessary for companies to demonstrate that their models, particularly in the context of tasks like facial detection, are not biased? If so, do you have thoughts on how this could be standardized and implemented?\n",
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"* Do you have ideas for other ways to address issues of bias, particularly in terms of the training data?\n",
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"\n",
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"**Try to optimize your model to achieve improved performance. To enter the competition, please upload the following to the lab submission site for the Debiasing Faces Lab ([submission upload link](https://www.dropbox.com/request/KGct8m2IyOBVvIoQdef3)).**\n",
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"**Try to optimize your model to achieve improved performance. To enter the competition, please upload the following to the lab submission site for the Debiasing Faces Lab ([submission upload link](https://www.dropbox.com/request/dJZUEoqGLB43JEKzzqIc)).**\n",
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"\n",
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"* Jupyter notebook with the code you used to generate your results;\n",
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"* copy of the bar plot from section 2.6 showing the performance of your model;\n",
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