Data science is a broad topic. It is the best to approach Data Science depending on the experience as a Data Scientist and what you really want to achieve with Data Science. That is why I divide different data science topics into separate categories, so it is easier for you to find them.
Starting with Data Science
Are you a programmer that wants to upgrade his portfolio and become a Data Scientist or maybe you want to do a profession switch?
Have you heard that Data Science is a demanding profession and want to jump into it? This is a great place to start learning about Data Science and how to become a great Data Scientist.
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Advanced Data Science
You are already proficient in many Machine learning techniques, and you have applied machine learning to real business problems. Here you will find more advanced machine learning projects that I have worked on and probably still working on.
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Experiences from work as a data scientist
We all build our career by solving different problems. Those problems can be related to Machine learning, something with data science, or simply with the type of work you are doing or more common, your manager. Here I want to pass on my thoughts of what kind of problems I faced while I am working as a Data scientist every day.
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Building Data Science Projects
You have an idea that you want to solve using Machine learning and AI, but you don’t know where and how to start. I try to give you some Ideas on how to start four Data Science or Machine learning project.
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Data Science for Marketing
I have worked on solving Marketing problems since 2013. Building solution to solve Marketing problematics can be really challenging, not only because of the data that you have to work with but also because you have to explain what your model is doing to people that have never seen Machine Learning model before. I do this every day now.
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When you work on a project with limited resources or you work in an early stage startup, you have to make your hands dirty with some Data Engineering before you start building Machine learning models. Here I try to pass on knowledge for problems that I face regularly and I found them critical at some point in time. You will read about Databases, SQL, SQL Server Analytics, SSIS end so on.
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Machine Learning in the cloud
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