Youtor
Maximum Likelihood as Minimizing KL Divergence
>> YOUR LINK HERE: ___ http://youtube.com/watch?v=HUsznqt2V5I
The Kullback-Leibler-Divergence measure how far two probability distributions are apart . We can conveniently calculate it by the help of TensorFlow Probability. Here are the notes: https://raw.githubusercontent.com/Cey... • The KL-Divergence is especially relevant when we want to fit one distribution against another. It has multiple applications in Probabilistic Machine Learning and Statistics. In a later video, we will use it to derive Variational Inference, a powerful tool to fit surrogate posterior distributions. • ------- • 📝 : Check out the GitHub Repository of the channel, where I upload all the handwritten notes and source-code files (contributions are very welcome): https://github.com/Ceyron/machine-lea... • 📢 : Follow me on LinkedIn or Twitter for updates on the channel and other cool Machine Learning Simulation stuff: / felix-koehler and / felix_m_koehler • 💸 : If you want to support my work on the channel, you can become a Patreon here: / mlsim • ------- • Timestamps: • 0:00 Opening • 0:15 Intuition • 03:21 Definition • 05:28 Example • 13:29 TensorFlow Probability
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