Scatter pairplot is a visualization of pairwise relationships in a dataset and is the first step for effective feature selection

Image by Benjamin O. Tayo

Understanding the most important features to use is crucial for developing a model that performs well. Knowing which features to consider requires experimentation, and proper visualization of your data can help clarify your initial selections. The scatter pairplot is a great place to start.

The scatter pairplot is a visualization of pairwise relationships in a dataset and is the first step for effective feature selection. It provides a qualitative analysis of the pairwise correlation between features and is a powerful tool for feature selection and dimensionality reduction. …

Mathematics remains a major hindrance for beginners trying to get into data science

Image by Benjamin O. Tayo

Most beginners interested in getting into the field of data science are always concerned about the math requirements. Data science is a very quantitative field that requires advanced mathematics. But to get started, you only need to master a few math topics. In this series of articles, we will dive deep and discuss the essential math topics that must be reviewed before embarking on a data science journey. We will begin with functions. The topics to be covered in the series are:

  • Functions
  • Statistics and Probability
  • Linear Algebra


Most of basic data science is focused on finding the relationship between…

How I reinvented myself to remain as a top writer on medium

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When I wrote my first article on medium back in June 2018, I hardly would have imagine that I was launching the beginning of a writing career. Before summer 2018, I didn’t even know that a blogging website like medium existed. I was working with a group of friends on a data science project, and one of my team members shared a tutorial which he found on medium to help guide us while we tackled the project at hand. As I navigated through medium, I just fell in love with the platform. …

Proper knowledge about personal finance will help you increase your risk tolerance and overcome investment fears

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Disclaimer: This article is meant to share some basic knowledge about personal finance and wealth building, and in no way should be considered as investment advice.

Investing is a subject that a lot of people are uncomfortable talking about. Some view investing as as type of gambling activity with only a small chance of success. However, investing is inevitable for financial planning and wealth building. The best saving accounts, even money market accounts have interest rates (< 1%) that can’t even keep up with inflation (~ 3% annually). Also, as we get old, cost of living will increase as our…

9 Tips to enable you become a top writer and earner

Figure 1. Screenshot by author.

I received the April and May $500 bonus from medium. The message from medium read like this:

Benjamin: This past month, you were in the top 1,000 writers in the Partner Program. Congratulations! To celebrate your achievement, we’re rewarding you with a $500 bonus.

Unlike in April (2021) where the top 1,000 writers each received a $500 bonus, in May (2021), the bonus was distributed into 3 bonus categories or tiers as shown below:

Data Science

5 Reasons why the journey to data science can be compared to a marathon

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I’ve seen numerous posts, books, or ads about learning data science in 4 weeks or in one year. While it is possible to learn the basics (black-box knowledge) of data science within a short period of time, it takes a lot more to really master the theoretical and practical aspects of data science. That being said, the journey to become a data scientist is analogous to a marathon, not a sprint. Here are 5 reasons why:

1. Academic knowledge is good, but more practical knowledge is essential

The proliferation of data science programs, whether from well-known colleges or from massive open online platforms means there are lots of options to choose…

Is blogging a good return on investment of your time?

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I recently wrote a data science blog, entitled: Essential Linear Algebra for Data Science and Machine Learning, which can be found using this link:

The basic idea of the article is to illustrate the application of linear algebra in data science and machine learning.

Steps for writing the blog

Data collection: The data was collected from google finance, organized and saved as a csv file (tech-stocks-04–2021.csv), which was then uploaded on github.

Writing of code: A Jupyter notebook code was developed for analyzing the data and for producing all data visualizations and tables.

Preparation of article draft: The output from the Jupyter notebook was used…

Data Science, Machine Learning

Beginners or established data science practitioners must develop a strong familiarity with the essential concepts in linear algebra

Image by Benjamin O. Tayo.

Linear Algebra is a branch of mathematics that is extremely useful in data science and machine learning. Linear algebra is the most important math skill in machine learning. Most machine learning models can be expressed in matrix form. A dataset itself is often represented as a matrix. Linear algebra is used in data preprocessing, data transformation, and model evaluation. Here are the topics you need to be familiar with:

  • Vectors
  • Matrices
  • Transpose of a matrix
  • Inverse of a matrix
  • Determinant of a matrix
  • Trace of a matrix
  • Dot product
  • Eigenvalues
  • Eigenvectors

In this article, we illustrate the application of linear…

Job roles and required qualifications for prospective data scientists varies from organization to organization

Image by Benjamin O. Tayo

Everyone pretty much have an idea of what data scientists do. They leverage data for smarter, more informed decisions, and better products. They use data to build models that help companies to understand their products and growth, identify opportunities, and execute ideas that could increase efficiency and profits.

Data scientists can work in different sectors such as technology, energy, government, healthcare, academia, business, etc. Depending on the organization they work for, the role of a data scientist may vary from sector to sector. With the unprecedented rate at which data is being produced, companies and organizations are seeking new ways…

Outline for teaching yourself the basics of data science in 7 weeks

Image by Benjamin O. Tayo


For individuals wishing to learn the basics of data science, this article discusses some of the topics to be familiar with in order to master the fundamentals of data science. The list of suggested topics is not all-encompassing, but it includes topics that if carefully studied, would enable the learner to understand the foundations of data science, and should be able to start applying the knowledge learned to simple data science tasks.

The essential topics have been organized so that completion could be achieved in 7 weeks of intensive studies (10–20 hours per week). For individuals with a solid background…

Benjamin Obi Tayo Ph.D.

Physicist, Data Science Educator, Writer. Interests: Data Science, Machine Learning, AI, Python & R, Personal Finance Analytics, Materials Sciences, Biophysics

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