I am going to explain to you about getting started with Kaggle and making use of it to master your data science skills. Kaggle is one of the world’s largest community of data scientists and machine learning specialists.
This article will discuss the use of twint, including how to installtwint; how to look up user information, and searching historical tweets given conditions. After gathering the data, I will use the Pandas library to clean the data and derive insights.
In this post, we will cover 11 very important operations that cover almost all you need to know about Python lists.
We talked about: The AI technology behind his work at Lindera; His career pathHow it is to be a research-centered scientist; How to become a good leader; Why it is important to approach AI research from a business perspective.
Top Data Science Candidates receive many opportunity options daily. To avoid candidates fall through the cracks, you must consider these four things.
Are you aspiring to be a data scientist but not sure what it takes to secure a job? In this article, I am going to outline the expectation of recruiters from the potential candidates in terms of: Tools specific knowledge; Technical Skills; Soft Skills.
What we do (mostly I) at home as a Data Scientist. Here, I am going to share my own experience as a Data Scientist who is still experiencing working at home.
In this article, I will present the 22 questions in fundamental statistics that you may encounter during interviews.
In this article, I will be sharing what kind of roles exists in the industry infamously referred to as “data scientists” and debunking the rockstar data scientists requirements.
Difference Between Linear & Logistic Regression — A Common Data Scientist Interview Question
I tried to establish several principles of ethics that will guide me and inform the good data science practice. I also wrote a draft referring to the Hippocratic oath for Data Science that I will share with you in this article.
Starbucks Customer Segmentation Analysis with Python. I took on this project to understand how one could use data to inform business decisions and it was a great learning process.
How to Build the Perfect CV to Land a Data Science Role. In this post, you’ll find expert tips, examples, and takeaways to make a resume that’s good enough for the job you really want.
How to think about explainability in your machine learning models? A step-by-step guide to understanding model behaviour, explaining predictions, and building trustworthy models
Data Scientist Must Know: Business x Statistics. Why integration between business and statistic is essential for Data Scientist.
Know the Difference Between a Data Scientist and a Data Engineer. Big data engineer certification and data science certification programs stand resourceful for those looking to get into the data realm.
I have mentioned the step-by-step guide to learn Data Science. I have explained the depth of knowledge required to reach different levels of expertise in Data Science.
In this post I talk about what I was doing before becoming a Data Scientist, how did I become one and what is it like being one.
In this article I wont be just telling you the differences but I will also explain when and why you should chose Data Engineer as your career choice.
Ain’t No Such a Thing as a ‘Citizen Data Scientist’. The strategy to undermine the difficulty in doing data science