I will use the GitHub Pages to write what am I generally experiencing as Machine Learning Analyst and Prediction Engineer.
Note that I am avoding to use word Data Scientist. The reason is twofold:
- the term became an "unicorn" position and the buzz-word
- real Data Scientist should have knowledge of the following things:
- good understanding of math and statistics
- programming languages: Python/R, SQL, etc.
- knowledge of machine learning models
- business/industry-relevant domain knowledge
I could say that I cover the first three with more-or-less some experience (SQL being the most vague one). However, as applied physicsist I do not have real money-making domain. Hence I do not see myself as Data Scientist (yet!).
A0 poster-like summary of Andriy Burkov's book The Hundred-Page Machine Learning Book. There is high-resolution .pdf, .png and .jpg file as the source file itself.
>> >>Click here<< << for more details.
Helpful AWS+Docker trick/tips for Natural Language Processing course, that is part of the Coursera's Advanced Machine Learning specialization.
>> >>Click here<< << for more details.
Helpful coding insights for Reinforcement Learning course, that is part of the Coursera's Advanced Machine Learning specialization.
>> >>Click here<< << for more details.