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adds contents table in learning notebook
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learning.ipynb

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"\n",
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"In Reinforcement Learning the agent learns from a series of reinforcements—rewards or punishments.\n",
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"\n",
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"**Example**: Let's talk about an agent to play the popular Atari game—[Pong](http://www.ponggame.org). We will reward a point for every correct move and deduct a point for every wrong move from the agent. Eventually, the agent will figure out its actions prior to reinforcement were most responsible for it."
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"**Example**: Let's talk about an agent to play the popular Atari game—[Pong](http://www.ponggame.org). We will reward a point for every correct move and deduct a point for every wrong move from the agent. Eventually, the agent will figure out its actions prior to reinforcement were most responsible for it.\n",
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"\n",
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"## Contents\n",
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"\n",
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"* Explanations of learning module\n",
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"* Practical Machine Learning Task\n",
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" * MNIST handwritten digits classification\n",
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" * Loading and Visualising digits data\n",
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" * Naive kNN classifier\n",
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" * Overfitting and how to avoid it\n",
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" * Train-Test split\n",
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" * Crossvalidation\n",
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" * Regularisation\n",
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" * Email spam detector"
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]
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},
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{

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