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…

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. …

Learn cause and effect analysis with these packages — Causal Analysis is a field within experimental statistics to prove and establish the cause and effect relationship. In statistics, using statistical algorithms to infer causality within the dataset under the strict assumption is called Exploratory causal analysis (ECA). ECA, in turn, is a way to prove causation with more controllable…

Explore data in a more interactive way — Data analysis is a staple activity for any data person and is required to understand what we are working on. To help the data analysis process, we have used the Python language for an easier workflow. However, sometimes we want a more interactive way to explore data. …

Machine Learning Automation is part of data scientist work — Machine learning is only valuable when made into production, yet the process is not ending there. Our machine learning model is required to be monitored constantly and controlled automatically. The practice of deploying and maintaining machine learning models in production is MLOps. The narrative of MLOps came from the old…