mhjensen
251 lines
14 KiB
HTML
251 lines
14 KiB
HTML
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'sections': [('What? Me worry? No final exam in this course!',
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('What did I learn in school this year?', 2, None, '___sec1'),
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('Best wishes to you all and thanks so much for your heroic '
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<a href="#" class="dropdown-toggle" data-toggle="dropdown">Contents <b class="caret"></b></a>
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<ul class="dropdown-menu">
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<!-- navigation toc: --> <li><a href="._summary-bs001.html#___sec0" style="font-size: 80%;">What? Me worry? No final exam in this course!</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs002.html#___sec1" style="font-size: 80%;">What did I learn in school this year?</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs003.html#___sec2" style="font-size: 80%;">Topics we have covered this year</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs004.html#___sec3" style="font-size: 80%;">Statistical analysis and optimization of data</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs005.html#___sec4" style="font-size: 80%;">Machine learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs006.html#___sec5" style="font-size: 80%;">Learning outcomes and overarching aims of this course</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs007.html#___sec6" style="font-size: 80%;">Perspective on Machine Learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs008.html#___sec7" style="font-size: 80%;">Machine Learning Research</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs009.html#___sec8" style="font-size: 80%;">Starting your Machine Learning Project</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs010.html#___sec9" style="font-size: 80%;">Choose a Model and Algorithm</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs011.html#___sec10" style="font-size: 80%;">Preparing Your Data</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs012.html#___sec11" style="font-size: 80%;">Which Activation and Weights to Choose in Neural Networks</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs013.html#___sec12" style="font-size: 80%;">Optimization Methods and Hyperparameters</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs014.html#___sec13" style="font-size: 80%;">Resampling</a></li>
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<!-- navigation toc: --> <li><a href="#___sec14" style="font-size: 80%;">Other courses on Data science and Machine Learning at UiO</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs016.html#___sec15" style="font-size: 80%;">Additional courses of interest</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs017.html#___sec16" style="font-size: 80%;">What's the future like?</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs018.html#___sec17" style="font-size: 80%;">Bayesian Machine Learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs019.html#___sec18" style="font-size: 80%;">Reinforcement Learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs020.html#___sec19" style="font-size: 80%;">Transfer learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs021.html#___sec20" style="font-size: 80%;">Adversarial learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs022.html#___sec21" style="font-size: 80%;">Dual learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs023.html#___sec22" style="font-size: 80%;">Distributed machine learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs024.html#___sec23" style="font-size: 80%;">Meta learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs025.html#___sec24" style="font-size: 80%;">The Challenges Facing Machine Learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs026.html#___sec25" style="font-size: 80%;">Explainable machine learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs027.html#___sec26" style="font-size: 80%;">Quantum machine learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs028.html#___sec27" style="font-size: 80%;">Quantum machine learning algorithms based on linear algebra</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs029.html#___sec28" style="font-size: 80%;">Quantum reinforcement learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs030.html#___sec29" style="font-size: 80%;">Quantum deep learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs031.html#___sec30" style="font-size: 80%;">Social machine learning</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs032.html#___sec31" style="font-size: 80%;">The last words?</a></li>
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<!-- navigation toc: --> <li><a href="._summary-bs033.html#___sec32" style="font-size: 80%;">Best wishes to you all and thanks so much for your heroic efforts this semester</a></li>
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</ul>
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</li>
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<p> </p><p> </p><p> </p> <!-- add vertical space -->
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<a name="part0015"></a>
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<!-- !split -->
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<h2 id="___sec14" class="anchor">Other courses on Data science and Machine Learning at UiO </h2>
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<p>
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The link here <a href="https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/" target="_self"><tt>https://www.mn.uio.no/english/research/about/centre-focus/innovation/data-science/studies/</tt></a> gives an excellent overview of courses on Machine learning at UiO.
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<ol>
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<li> <a href="http://www.uio.no/studier/emner/matnat/math/STK2100/index-eng.html" target="_self">STK2100 Machine learning and statistical methods for prediction and classification</a>.</li>
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<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN3050/index-eng.html" target="_self">IN3050/IN4050 Introduction to Artificial Intelligence and Machine Learning</a>. Introductory course in machine learning and AI with an algorithmic approach.</li>
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<li> <a href="http://www.uio.no/studier/emner/matnat/math/STK-INF3000/index-eng.html" target="_self">STK-INF3000/4000 Selected Topics in Data Science</a>. The course provides insight into selected contemporary relevant topics within Data Science.</li>
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<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN4080/index.html" target="_self">IN4080 Natural Language Processing</a>. Probabilistic and machine learning techniques applied to natural language processing.</li>
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<li> <a href="https://www.uio.no/studier/emner/matnat/math/STK-IN4300/index-eng.html" target="_self">STK-IN4300 – Statistical learning methods in Data Science</a>. An advanced introduction to statistical and machine learning. For students with a good mathematics and statistics background.</li>
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<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN-STK5000/index-eng.html" target="_self">IN-STK5000 Adaptive Methods for Data-Based Decision Making</a>. Methods for adaptive collection and processing of data based on machine learning techniques.</li>
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<li> <a href="https://www.uio.no/studier/emner/matnat/ifi/IN5400/" target="_self">IN5400/INF5860 – Machine Learning for Image Analysis</a>. An introduction to deep learning with particular emphasis on applications within Image analysis, but useful for other application areas too.</li>
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<li> <a href="https://www.uio.no/studier/emner/matnat/its/TEK5040/" target="_self">TEK5040 – Dyp læring for autonome systemer</a>. The course addresses advanced algorithms and architectures for deep learning with neural networks. The course provides an introduction to how deep-learning techniques can be used in the construction of key parts of advanced autonomous systems that exist in physical environments and cyber environments.</li>
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</ol>
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<p>
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