Identify changes in the slope using machine learning
<p>I want to get my hands dirty with some machine learning, and I finally have a problem which seems like a good beginner project. However, despite reading a lot about the subject I am unsure how to get started, and what my basic approach should be.</p>

<p><a href="http://imgur.com/a/kclpm" rel="nofollow noreferrer">I have a dataset which should look like this</a>.</p>

<p><a href="https://i.stack.imgur.com/X1Au4.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/X1Au4.png" alt="enter image description here"></a></p>

<p>a real dataset looks more like this:</p>

<p><a href="https://i.stack.imgur.com/TWRsr.jpg" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/TWRsr.jpg" alt="enter image description here"></a></p>

<p>I want to identify the points in the red circles (on the first image), and be robust against occasional artifacts like the one in the blue circle.</p>

<p>I sounds like a really easy task. However, the is quite a lot of noise in the raw data. My current implementation is pretty traditional. It blurs the data and compares the first and second derivative to some estimated threshold values. This approach works, but can "only" identify the points with ~99.7% accuracy, but since I do around 100.000 measurements a day I would love to increase this number.</p>

<p>So, this is what I have:</p>

<ol>
<li>All the datasets I want/need</li>
<li>A pretty good model of how the data should look.</li>
<li>A pretty good training set, using my existing algorithm (the outlines can be fixed manually)</li>
</ol>

<p>However, <strong>I do not have a basic idea how what approach I should use.</strong> I feels like none of the material I've read on machine learning fit's this problem.</p>

<p>Can someone help me with the super high level approach to solve this problem?</p>