Data Science and Machine learning basics
There is a lot of interest in Data science and Machine learning, Let’s get a quick grasp on what these terms mean and what we need to learn to be a part of this profession.
- Is about coding, and doing mathematics on data.
- Applying algorithms to data to get productive outcomes.
- Finding patterns that can be exploited for business outcomes.
- Real-time applications like chatbots, image recognition, and product choice suggestions based on customer behavior, are irrelevant to specific domain expertise.
- Is a combination of Coding, Statistics, and Domain expertise.
- a similar job like research lab scientist may be true to an extent, but not completely,
- If you are sanitizing the data for analysis by writing a program you are doing the data science job, usually, python or R language is used along with SQL may be (an example if you want to pipe the data to a database)
- If you are managing the storage of large amounts of data, you are doing the data-science job.
- Deriving product offerings from the data after applying machine learning and algorithms, this in term monetizes the data.
- Data science is a very diverse field, with many different tools, and many different teams, like coding, statistics, design, presentation, etc…
- at the end of the day, each data science project is teamwork of coders, statisticians, engineers, business, and management.
Below is an excellent video explaining the basics
Also please check on “Failure and Jealousy“