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mhjensen committed Nov 23, 2024
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2,
None,
'xgboost-extreme-gradient-boosting'),
('Regression Case', 2, None, 'regression-case'),
('Xgboost on the Cancer Data',
2,
None,
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<!-- navigation toc: --> <li><a href="._week48-bs021.html#gradient-boosting-examples-of-regression" style="font-size: 80%;">Gradient Boosting, Examples of Regression</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs022.html#gradient-boosting-classification-example" style="font-size: 80%;">Gradient Boosting, Classification Example</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs023.html#xgboost-extreme-gradient-boosting" style="font-size: 80%;">XGBoost: Extreme Gradient Boosting</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs024.html#regression-case" style="font-size: 80%;">Regression Case</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs025.html#xgboost-on-the-cancer-data" style="font-size: 80%;">Xgboost on the Cancer Data</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs026.html#gradient-boosting-making-our-own-code-for-a-regression-case" style="font-size: 80%;">Gradient boosting, making our own code for a regression case</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs027.html#summary-of-course" style="font-size: 80%;">Summary of course</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs028.html#what-me-worry-no-final-exam-in-this-course" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs029.html#topics-we-have-covered-this-year" style="font-size: 80%;">Topics we have covered this year</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs030.html#statistical-analysis-and-optimization-of-data" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs031.html#machine-learning" style="font-size: 80%;">Machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs032.html#learning-outcomes-and-overarching-aims-of-this-course" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs033.html#perspective-on-machine-learning" style="font-size: 80%;">Perspective on Machine Learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs034.html#machine-learning-research" style="font-size: 80%;">Machine Learning Research</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs035.html#starting-your-machine-learning-project" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs036.html#choose-a-model-and-algorithm" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs037.html#preparing-your-data" style="font-size: 80%;">Preparing Your Data</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs038.html#which-activation-and-weights-to-choose-in-neural-networks" style="font-size: 80%;">Which activation and weights to choose in neural networks</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs039.html#optimization-methods-and-hyperparameters" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs040.html#resampling" style="font-size: 80%;">Resampling</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs041.html#other-courses-on-data-science-and-machine-learning-at-uio" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs042.html#additional-courses-of-interest" style="font-size: 80%;">Additional courses of interest</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs043.html#what-s-the-future-like" style="font-size: 80%;">What's the future like?</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs044.html#types-of-machine-learning-a-repetition" style="font-size: 80%;">Types of Machine Learning, a repetition</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs045.html#why-boltzmann-machines" style="font-size: 80%;">Why Boltzmann machines?</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs046.html#boltzmann-machines" style="font-size: 80%;">Boltzmann Machines</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs047.html#some-similarities-and-differences-from-dnns" style="font-size: 80%;">Some similarities and differences from DNNs</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs048.html#boltzmann-machines-bm" style="font-size: 80%;">Boltzmann machines (BM)</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs049.html#a-standard-bm-setup" style="font-size: 80%;">A standard BM setup</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs050.html#the-structure-of-the-rbm-network" style="font-size: 80%;">The structure of the RBM network</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs051.html#the-network" style="font-size: 80%;">The network</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs052.html#goals" style="font-size: 80%;">Goals</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs053.html#joint-distribution" style="font-size: 80%;">Joint distribution</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs054.html#network-elements-the-energy-function" style="font-size: 80%;">Network Elements, the energy function</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs055.html#defining-different-types-of-rbms" style="font-size: 80%;">Defining different types of RBMs</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs056.html#more-about-rbms" style="font-size: 80%;">More about RBMs</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs057.html#autoencoders-overarching-view" style="font-size: 80%;">Autoencoders: Overarching view</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs058.html#bayesian-machine-learning" style="font-size: 80%;">Bayesian Machine Learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs059.html#reinforcement-learning" style="font-size: 80%;">Reinforcement Learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs060.html#transfer-learning" style="font-size: 80%;">Transfer learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs061.html#adversarial-learning" style="font-size: 80%;">Adversarial learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs062.html#dual-learning" style="font-size: 80%;">Dual learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs063.html#distributed-machine-learning" style="font-size: 80%;">Distributed machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs064.html#meta-learning" style="font-size: 80%;">Meta learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs065.html#the-challenges-facing-machine-learning" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs066.html#explainable-machine-learning" style="font-size: 80%;">Explainable machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs067.html#quantum-machine-learning" style="font-size: 80%;">Quantum machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs068.html#quantum-machine-learning-algorithms-based-on-linear-algebra" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs069.html#quantum-reinforcement-learning" style="font-size: 80%;">Quantum reinforcement learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs070.html#quantum-deep-learning" style="font-size: 80%;">Quantum deep learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs071.html#social-machine-learning" style="font-size: 80%;">Social machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs072.html#the-last-words" style="font-size: 80%;">The last words?</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs073.html#best-wishes-to-you-all-and-thanks-so-much-for-your-heroic-efforts-this-semester" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs024.html#xgboost-on-the-cancer-data" style="font-size: 80%;">Xgboost on the Cancer Data</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs025.html#gradient-boosting-making-our-own-code-for-a-regression-case" style="font-size: 80%;">Gradient boosting, making our own code for a regression case</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs026.html#summary-of-course" style="font-size: 80%;">Summary of course</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs027.html#what-me-worry-no-final-exam-in-this-course" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs028.html#topics-we-have-covered-this-year" style="font-size: 80%;">Topics we have covered this year</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs029.html#statistical-analysis-and-optimization-of-data" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs030.html#machine-learning" style="font-size: 80%;">Machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs031.html#learning-outcomes-and-overarching-aims-of-this-course" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs032.html#perspective-on-machine-learning" style="font-size: 80%;">Perspective on Machine Learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs033.html#machine-learning-research" style="font-size: 80%;">Machine Learning Research</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs034.html#starting-your-machine-learning-project" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs035.html#choose-a-model-and-algorithm" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs036.html#preparing-your-data" style="font-size: 80%;">Preparing Your Data</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs037.html#which-activation-and-weights-to-choose-in-neural-networks" style="font-size: 80%;">Which activation and weights to choose in neural networks</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs038.html#optimization-methods-and-hyperparameters" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs039.html#resampling" style="font-size: 80%;">Resampling</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs040.html#other-courses-on-data-science-and-machine-learning-at-uio" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs041.html#additional-courses-of-interest" style="font-size: 80%;">Additional courses of interest</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs042.html#what-s-the-future-like" style="font-size: 80%;">What's the future like?</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs043.html#types-of-machine-learning-a-repetition" style="font-size: 80%;">Types of Machine Learning, a repetition</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs044.html#why-boltzmann-machines" style="font-size: 80%;">Why Boltzmann machines?</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs045.html#boltzmann-machines" style="font-size: 80%;">Boltzmann Machines</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs046.html#some-similarities-and-differences-from-dnns" style="font-size: 80%;">Some similarities and differences from DNNs</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs047.html#boltzmann-machines-bm" style="font-size: 80%;">Boltzmann machines (BM)</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs048.html#a-standard-bm-setup" style="font-size: 80%;">A standard BM setup</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs049.html#the-structure-of-the-rbm-network" style="font-size: 80%;">The structure of the RBM network</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs050.html#the-network" style="font-size: 80%;">The network</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs051.html#goals" style="font-size: 80%;">Goals</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs052.html#joint-distribution" style="font-size: 80%;">Joint distribution</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs053.html#network-elements-the-energy-function" style="font-size: 80%;">Network Elements, the energy function</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs054.html#defining-different-types-of-rbms" style="font-size: 80%;">Defining different types of RBMs</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs055.html#more-about-rbms" style="font-size: 80%;">More about RBMs</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs056.html#autoencoders-overarching-view" style="font-size: 80%;">Autoencoders: Overarching view</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs057.html#bayesian-machine-learning" style="font-size: 80%;">Bayesian Machine Learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs058.html#reinforcement-learning" style="font-size: 80%;">Reinforcement Learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs059.html#transfer-learning" style="font-size: 80%;">Transfer learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs060.html#adversarial-learning" style="font-size: 80%;">Adversarial learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs061.html#dual-learning" style="font-size: 80%;">Dual learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs062.html#distributed-machine-learning" style="font-size: 80%;">Distributed machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs063.html#meta-learning" style="font-size: 80%;">Meta learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs064.html#the-challenges-facing-machine-learning" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs065.html#explainable-machine-learning" style="font-size: 80%;">Explainable machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs066.html#quantum-machine-learning" style="font-size: 80%;">Quantum machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs067.html#quantum-machine-learning-algorithms-based-on-linear-algebra" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs068.html#quantum-reinforcement-learning" style="font-size: 80%;">Quantum reinforcement learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs069.html#quantum-deep-learning" style="font-size: 80%;">Quantum deep learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs070.html#social-machine-learning" style="font-size: 80%;">Social machine learning</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs071.html#the-last-words" style="font-size: 80%;">The last words?</a></li>
<!-- navigation toc: --> <li><a href="._week48-bs072.html#best-wishes-to-you-all-and-thanks-so-much-for-your-heroic-efforts-this-semester" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>

</ul>
</li>
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<li><a href="._week48-bs008.html">9</a></li>
<li><a href="._week48-bs009.html">10</a></li>
<li><a href="">...</a></li>
<li><a href="._week48-bs073.html">74</a></li>
<li><a href="._week48-bs072.html">73</a></li>
<li><a href="._week48-bs001.html">&raquo;</a></li>
</ul>
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