probabilistic model: videos

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1. 1▶14 Review and outlook (MLVU2018)VU Machine Learning 2018Notes
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2. 2▶13 Reinforcement Learning: Policy Gradients, Q Learning, AlphaGo (MLVU2018)VU Machine Learning 2018Notes
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3. 3▶12 Matrix Models: Recommender systems and Matrix factorization (MLVU2018)VU Machine Learning 2018Notes
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4. 4▶11 Models for Sequential Data: Markov Models, Word2Vec, RNNs and LSTMs.VU Machine Learning 2018Notes
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5. 5▶10 Tree Models and Ensembles: Decision Trees, Boosting, Bagging, Gradient Boosting (MLVU2018)VU Machine Learning 2018Notes
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6. 6▶09 Deep Learning 2: GANs, Variational Autoencoders (MLVU2018)VU Machine Learning 2018Notes
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7. 7▶08 Probabilistic Models 2, Normal Distributions, Gaussian Mixtures and EM (MLVU2018)VU Machine Learning 2018Notes
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8. 8▶07 Linear Models 2: Support Vector Machines, the Kernel trick (MLVU2018)VU Machine Learning 2018Notes
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9. 9▶06 Deep Learning 1: Neural networks, Convolutional layers (MLVU2018)VU Machine Learning 2018Notes
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10. 10▶05 Probabilistic Models 1: Naive Bayes, Entropy, Logistic Regression (MLVU2018)VU Machine Learning 2018Notes
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