I learnt about types of machine learning: Supervised– learns from previous experience, collects the data and produce from that same data. Reinforcement -reward for a correct decision . Unsupervised – finds unknown patterns in the given data . I found it interesting that genetic algorithm and reinforcement learning work on the same principles, that they are inspired by nature and they work on finding the ‘good solution’ according to some pre-defined concept of ‘goodness’. I also learnt to represent belief using probabilities, Bayes Rule to calculate the probabilities.
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