There&#x27;s a key statement here that most will either miss or never reach. The second last paragraph<p>&gt; Machine Learning Automation<p>Tuning models is a pain, and if you don&#x27;t understand the model and all its parameters (like most software engineers who&#x27;s job is the write software and not build models!) it takes time and can be immensely frustrating. Randal Olson[1] just announced TPOT[2], a Python tool that &quot;automatically creates and optimized machine learning pipelines using genetic programming&quot;. This is going to be a huge lever for engineers wanting to experiment&#x2F;implement with ML algorithms.<p>[1] <a href="http:&#x2F;&#x2F;www.randalolson.com&#x2F;2016&#x2F;05&#x2F;08&#x2F;tpot-a-python-tool-for-automating-data-science&#x2F;" rel="nofollow">http:&#x2F;&#x2F;www.randalolson.com&#x2F;2016&#x2F;05&#x2F;08&#x2F;tpot-a-python-tool-for...</a>
[2] <a href="https:&#x2F;&#x2F;github.com&#x2F;rhiever&#x2F;tpot" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;rhiever&#x2F;tpot</a>