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    <title>python on Mari Galicer.</title>
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    <description>Recent content in python on Mari Galicer.</description>
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      <title>Machine learning in production with Flask, Twilio, Docker, and Google Cloud</title>
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      <pubDate>Fri, 08 Mar 2019 08:19:24 +0000</pubDate>
      
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      <description>The code for this project - excluding the model and training data, both of which are too big to upload - can be found on my Github.
It&amp;rsquo;s common to hear how powerful machine learning models are, but courses and tutorials usually stop short of showing you how to use them in real life. Here, I want to talk about how I was able to train and export an image classification model and set it up in a small web app using Flask, Twilio, and Docker, so that anyone can text images to the model and have them return a classification.</description>
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      <title>Dynamic Programming with Python</title>
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      <pubDate>Mon, 04 Feb 2019 02:20:11 +0000</pubDate>
      
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      <description>Today I worked on a LeetCode problem called House Robber: given an array of numbers, each representing the amount of money in the house, find the maximum amount of money you can rob without robbing neighboring houses.
Example:
Input: [1,2,3,1]
Output: 4
Explanation: Rob house 1 (money = 1) and then rob house 3 (money = 3). Total amount you can rob = 1 + 3 = 4.
Here, it looks like one easy solution might be to simply get the sums of the values at alternating indices and choose the max of those:</description>
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