As a data scientist/analyst, your job is to produce a report that contained many insights for business decisions. A report can be made by several useful tools such as Microsoft Excel, SAP, or customized with the programing language such as SAS, R, or Python. The result can be sent through internal email to a stakeholder or publish through the centralized dashboard.
Like everyone else, I am a data analyst who uses python for making a report or presentation in daily life. My usual assignment is to make an ad-hoc analysis within 2–3 hours to present to the management team.
We all have limited time in our life.
24 hours a day is relatively short if you have many things to achieve. We all dream about a productive life to get whatever we want to be done with ease.
However, life is not that easy and sends so many distractions to you, especially in 2020.
We all have social media, entertainment platform, online publications, etc., in our hands.
We can spend a day on it without bored. This is quite a difference compared to ten to twenty years ago.
The more time we spend on those distractions, the less number…
Machine learning pipeline is an essential part of data application. We build it to transform the raw data into an insightful prediction. The pipeline contains many steps such as data ingestion, data preprocessing, feature engineering, model fitting, and performance evaluation.
When data scientists start developing the ML pipeline, they try to build the whole pipeline fast and re-iterate the process by changing some hyper-parameter to get the best result. There are many hyper-parameters to tweak in this process.
It would be best if we can track the variation of those hyper-parameters. We will gain a deeper understanding of our ML…
Learning new trends from watching Korean Netflix’s series.
Spoiler alert: this article may contain information about this drama. Please feel free to skip it first if you have not watched it yet. But, if you don’t mind, let’s dive in!
Recently, I have watched the Netflix series called STARTUP. It’s a Korean drama that is on-air every SAT and SUN at 9 PM. The story is about a group of people who dream of establishing a startup business on their own.
Seem straightforward and not interested, right?
But, the exciting part is that the main character of this series is…
Data analytics, science, and engineering have grown much popularity in the last few years. It creates a new standard for the industry. Every company needs to invest or establish a data office within their organization.
It becomes standard in 2020 that you can have a prediction model for marketing leads, improving your check-in method with facial recognition., or looking at the elegant dashboard for making a business decision.
Exceptional use cases always come first to build the momentum of the analytics trend. Executives want to see a result before investing a massive amount of funds into a new direction.
I point out the importance and data quality issues in the previous article.
The quicker you realize the problem with your data, the better you can deliver a valid conclusion to drive the business.
When you have limited time to do the analysis, I hope this tutorial helps you like a checklist for ensuring the data condition before presenting to the audience.
Today I will show you the
code snippet for checking the data condition. The topics will cover units of analysis, missing values, duplicated records, Is your data makes sense, and truth changing over time.
The tutorial will be…
Hi everybody who is on the screen right now.
If you click on this story, I would like to thank you for reaching this page.
My name is Pathairush Seeda, or you can call me PAT. I was born in Thailand, and now I’m 28 years old. I’m a little brother from a Thai family.
I’m now working as a data scientist/engineer in Thailand's top 50 listed companies.
Also, I have been writing a Medium since October 2020. …
Time is limited, you have to spend it wisely
In the working world, everyone is in a rush. For the company's high-level executive, their calendar has been filled with a lot of important meetings.
Your 1-month project has to wrap up and present to them within 30 minutes or less. You have to give them all the needed information for a decision.
Everything has to be well prepared.
There is no room for any struggle, confusion, and ambiguity. The presentation deck needs to be clear and precise enough to move forwards with any actions.
How could I make…
Office workers, White-collar, and Salary-man describe those who work for a company to receive their wages at the end of each month. I am one of them, and I have worked as a salary-man for five years in Thailand.
Disclaimer: This is my thought. I am only 28 and work only in Thailand for my whole career life. The opinion on each topic could be varied depending on the reader’s location and culture.
The salary-man has a very stable behavior in their working life. They usually wake up in the morning to start working from 9 to 5 during weekdays…
Outstanding features can be used across many applications.
In my earlier article, I’ve already pointed out the 5 fundamental domains of feature engineering. It involves statistics, time, ratio, crossing, and geo-location domains.
To add value for our reader upon that point
Today, we will focus on the customer level feature. The customer level is the most entity we deal/talk about with. We often touch them individually through various campaigns.
Also, we can use the customer level feature for explaining the persona of the whole portfolio.
In this article, I will illustrate a
code snippet that you can make use of…