Data Science

Davido is a popular Nigerian-American singer and songwriter whom all have admired over the years because of his songs which are mostly thrilling and sensational. On the 31st of March 2023, Davido released his fourth album ‘Timeless’ with 17 track songs and total play duration of 49 minutes 12 seconds…

From data analyst to data engineer: why I made the transition — The growing need for technical skills In the ever-evolving field of data, many roles offer exciting growth, ownership, and innovation opportunities. Data engineers play a pivotal role in designing, building, and maintaining systems that enable organisations to effectively leverage their data. They work closely with data scientists to ensure that data is properly stored, secured, and…

Transitioning from SQL to Pandas to improve your data analysis workflow — Data analysts, engineers, and scientists alike are familiar with SQL. The querying language is still widely used across the board for working with relational databases of any kind. However, more and more nowadays, especially for data analysts the technical requirements are going up and people are expected to at least…

Introduction This report aims to provide a comprehensive analysis of healthcare facilities and their association with COVID-19 data. The analysis delves into key aspects such as the number of COVID-19 cases, mortality rates, occupancy rates, and the distribution of healthcare facilities across different states. …

The characteristics and value of reactive vs. proactive data teams — Fundamentally, there are two different types of data teams in this world. There are those who are reactive to the wants of the organization, and then there are those who proactively lead the organization towards its needs. The first is helpful, but a cost center. The second is a value…

Is Shiny the only way to develop web applications in R? That’s what I used to believe. But there are three powerful and easier alternatives that you should know about. Pros and Cons of each alternative: 1. OpenCpu Pros: you can use your R model as is without any change and plug…

I would like to present a step-by-step tutorial that demonstrates the process of developing applications for future stock price prediction. This tutorial serves as an opportunity for me to showcase my skills and capabilities to anyone who engages with me, allowing them to witness firsthand the results of my expertise. — In this project, we can learn various skills such as use of Streamlit, use of Prophet library and some basic knowledge of Stock Market Analysis.

Forget train_test_split: Pipeline, ColumnTransformer, FeatureUnion and FunctionTransformer are indispensable even if you use XGBoost or LGBM — Data preparation is famously the least-loved aspect of Data Science. If done right, however, it needn’t be such a headache. While scikit-learn has fallen out of vogue as a modelling library in recent years given the meteoric rise of PyTorch, LightGBM, and XGBoost, it’s still easily one of the best…