Hello all! I have writing on Medium for some time, but I just realized that I never create a complete About Me page — well, here it is. My name is Cornellius Yudha Wijaya and I am originally came from Indonesia. Currently, I have a full-time job as a Data…

Which pandas data frame EDA packages suit you? — As a data scientist, our work would always involve exploring data or often called Exploratory Data Analysis (EDA). The purposes of exploring data are to know our data better and grasp what we are dealing with. Previously, exploring data using the pandas data frame is a big hassle because we…

Synthetic data could help mitigate fraud cases — Fraud cases are common in any business industry and cause massive financial loss. Small or Big, every business would face the fraud problem whether they like it or not — as long as there are people with bad intentions. Many efforts have been exerted in machine learning fraud detection research…

Some of the time series packages you could add to your arsenal — Time series forecasting is a method in the statistics field to analyze historical data with a time component and create a prediction based on it. Some classic examples of time series forecasting methods are Moving Average, ARIMA, and Exponential Smoothing. These methods have been used for a long time and…

Know these packages to improve your data workflow — Feature engineering is the process of creating new features from the existing data. Whether we made a simple addition of two columns or combined more than a thousand features, the process is already considered feature engineering. The feature engineering process is inherently different from data cleaning. While feature engineering creates…

Don’t forget that bias could impact your project — When we talk about bias in the data science world, it will refer to the machine learning error in learning the input data and being unable to give the prediction objectively. If we make a human analogy, bias in machine learning could mean the model favours specific predictions/conditions over others…

Various Python packages for data people — Data is a vast field with big community support the technology development. Furthermore, Python has avid supporter that helps the data world become more accessible and brings value to the data workflow. Various Python packages have been developed to help data people in their works. In my experience, many useful…

Easy non-coding data scrapper tools for your work — Data is the central part of any machine learning project. That is why many efforts were exerted to collect data that could be used in the machine learning project. Without data, our project was unable to start. One of the most complex parts of data collection is to collect the…

Data labeling is crucial for the machine learning project's success — Data science projects involve a lot of data collection, cleaning, and processing. We did all the steps to ensure that the dataset quality was good for the machine learning training. Although, there is one specific important part of the data science project that could make or break the project: labeling. …