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I'm serious about this. Ultimately the job is just software development plus statistics.
If you are a software developer, work on your statistics.
If you're a statistician, learn to program.
Most people will have gaps in both of these sub-fields.
Do not, under any circumstances, take any online courses that include the phrases "data science" or "machine learning" in the title.
From own experience (switched to ML 1.5 years ago): 1. That software engineering skills are way more important than ML skills. 2. That you'd be spending more time on making presentation than doing ML (and it makes sense, it's very important to present statistics properly). 3. That most problems don't need good ML models. Something cheap and easy is often good enough. What you do need to be good, is data pipelines aro…
In industry, you also need to balance the amount of time and effort it takes to build your model against the incremental benefit.
From own experience (switched to ML 1.5 years ago): 1. That software engineering skills are way more important than ML skills. 2. That you'd be spending more time on making presentation than doing ML (and it makes sense, it's very important to present statistics properly). 3. That most problems don't need good ML models. Something cheap and easy is often good enough. What you do need to be good, is data pipelines aro…
Those are great points. Could you comment what resources you have used to learn ML?
Also there's a great Coursera course on ML for Kaggle: https://www.coursera.org/learn/competitive-data-science
I think once you finish it, you're better than 60% of silicon valley data scientists, no kidding.
From own experience (switched to ML 1.5 years ago): 1. That software engineering skills are way more important than ML skills. 2. That you'd be spending more time on making presentation than doing ML (and it makes sense, it's very important to present statistics properly). 3. That most problems don't need good ML models. Something cheap and easy is often good enough. What you do need to be good, is data pipelines aro…
Very good pointers. I would like to get in touch with you regarding how you transitioned to ML. I don't see a contact info in the profile. My email is in my profile. Pls let me know.
See this course to get into Kaggle: https://www.coursera.org/learn/competitive-data-science
Earlier quoted context omitted.
Very good pointers. I would like to get in touch with you regarding how you transitioned to ML. I don't see a contact info in the profile. My email is in my profile. Pls let me know.
Kaggle is more than enough to get started. I would hire anyone who's Master there. Probably not even need for Master, just enough knowledge to explain why that thing work and that would not. See this course to get into Kaggle: https://www.coursera.org/learn/competitive-data-science