Up to now, we tend to hear the success story of AI (Artificial Intelligence) or Machine Learning implementations. Some from many: Netflix (founded in 1997) is an entertainment company that consistently utilizes its analytics to track customers’ behavior from time to time, which has grown from $5 million in revenues…

It is very delighted when we have a clean-raw dataset, but in real cases, it is too good to be true. Mostly we have messy data here and there that need to handle, such as working with replacing its data type, filling in missing value, replacing or even removing the…

Presenting your data is always be a great way to strengthen your statement by revealing evidence-based information. No matter what is the environment, is it work or study, everyone tends to meet the occasion when they need to present with data. The challenges are sometimes the data itself is not…

I have one question in mind when seeing Covid had surging back in last June to August 2021 and having recovered pretty well in the last 2 months, my question was : ‘Are we safe enough to take domestic trips in Indonesia at least until the end of this year?’ …

Objective of this project is to predict anomaly detection in credit card transactions by applying various Machine/Deep Learning models and examine which best amongst all models. Dataset Description & Initial Planning The dataset used from Kaggle in csv format. The dataset contains transactions made by credit cards in September 2013 by European cardholders. This dataset…

This work aim is to create a multi linear regression model that could predict startup profit by knowing their R&D expense, marketing and administrative cost. I remember the time when I was working with the Ministry of Creative Economy back then in 2014, what we did were creating compact program…

One of essential work in any business area is targeting the right product for the right customers, so that it could boost up successful promotion, keeping up retention and subsequently increasing profit. This task is heavily relies on how well Data Scientist distinguish customers and create segmentation amongst all customer. …

This section is continuation process from earlier article Exploratory Data Analysis for Machine Learning on Successful Startup Worldwide. Brief of Dataset Description & Objective The dataset used is from Crunchbase in csv format, of which the data are worldwide start up companies recorded from 1902 until 2014. …

Start ups are supposed to be known for their innovation that arises from the gap of problem and solving, and also known for companies of growth seeking-business, so that the nature of business itself requires heavy funds and it is common to look for capital from a variety of sources…