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to Applied Data Analysis and Machine Learning","<span class=\"section-number\">9. </span>Recurrent Neural Networks","<span class=\"section-number\">11. </span>Data Analysis and Machine Learning:","<span class=\"section-number\">1. </span>Elements of Probability Theory and Statistical Data Analysis","<span class=\"section-number\">2. </span>Getting started, our first data and Machine Learning encounters","<span class=\"section-number\">3. </span>Linear Regression and more Advanced Regression Analysis","<span class=\"section-number\">4. </span>Logistic Regression","<span class=\"section-number\">5. </span>Neural networks, from the simple perceptron to deep learning","<span class=\"section-number\">6. </span>Support Vector Machines, overarching aims","<span class=\"section-number\">7. </span>Dimensionality Reduction","<span class=\"section-number\">8. </span>Convolutional Neural Networks","Introduction","Space, Time, Motion, Reference Frames  and Reminder on vectors and other mathematical quantities","Basic Steps of Scientific Investigations","Work, Energy, Momentum and Conservation laws","Harmonic Oscillator","Two-body Problems","Non-inertial Frames, Translation and Rotating Coordinate Systems","Content with notebooks","Content with notebooks","Introduction","Space, Time, Motion, Reference Frames  and Reminder on vectors and other mathematical quantities","Basic Steps of Scientific Investigations","Work, Energy, Momentum and Conservation laws","Harmonic Oscillator","Two-body Problems","Non-inertial Frames, Translation and Rotating Coordinate Systems","Content in Jupyter Book","PHY321, Classical Mechanics I, Michigan State University, Spring 2021","Code of Conduct","Contributing","LectureNotes","Content in Jupyter Book","Welcome to your Jupyter Book","Markdown Files","Content with notebooks","Markdown 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