1. Business Understanding: We should have clarity of what is the exact problem we are going to solve.
What is the problem that we are trying to solve? - Asking the right questions as a Data Scientist starts with understanding the goal of the business.
2. Analytical Approach: How can we use data to answer the question? We should decide the analytical approach to follow which can be of 4 types
- Descriptive
- Statistical
- Predictive
- Prescriptive
and it indicates the necessary data content, formats, and sources to be gathered
Data scientist use their analytical and technical capabilities to extract meaningful insight from data.
2. Machine Learning Engineer
Machine Learning engineer's final output is the working software, and their audience for this output consists of other software components that run automatically with minimal human supervision. The decisions are made by machines.
1. Boolean- The Boolean data type is a truth value, either True or False.
2, 3. Integer and Float - An integer is a positive or negative number without floating point. A float is a
positive or negative number with floating point
precision.
1. Trying to implement large projects from start to finish🧑💻: Well I am believer of "Learn Best by Doing". As I implement a project from scratch, I do get a lot of errors which ultimately teach me even more.
2. Working with friends 👬: Being a grauduate student, I am very much aware of the importance of working in groups. This method of learning improves my thinking and increases my confidence level.