Our latest articles about data science, machine learning, data analysis and programming. Enjoy!
Learn how to list installed packages in JupyterLab without using the terminal. Use a simple command or the Jupyter Package Manager for a quick, no-code solution. Save time and code smarter!
Machine Learning teaches computers to learn from data instead of following exact step-by-step instructions. The article explains different algorithms—from simple ones like K-Nearest Neighbors to advanced techniques like Gradient Boosting and AutoML—and discusses their benefits.
Learn how to easily delete packages in JupyterLab without using the terminal. Use a simple command or the Jupyter Package Manager for a quick, no-code solution. Save time and code smarter!
Discover two simple ways to install packages in JupyterLab without using the terminal. Learn how to use a notebook command or the Jupyter Package Manager to save time and avoid errors.
When using machine learning models like LightGBM, it is important to keep the order of columns consistent in your data, even when using Pandas DataFrames. I was surprised to find that changing the column order after training can affect prediction results, a detail even ChatGPT missed.
Explore 8 open-source AutoML frameworks that automate machine learning tasks, from algorithm selection to hyperparameter tuning. Find the perfect tool for your next project with expert insights.
Learn the top programming languages for Data Science! Discover how Python, R, and SQL help with data analysis, visualization, and machine learning. Find out which one suits your needs best!
In this post, I will explore the evolution of no-code data science, discuss its benefits and pitfalls, and introduce a solution I am building to simplify data analysis for everyone.
Learn how to install and manage Python packages using pip. This article covers setting up virtual environments, installing packages, updating them, and managing packages in Jupyter Notebooks to make your projects easier!
Compare Python packages for data visualization, including Matplotlib, Seaborn, Plotly, and more. Learn their features, strengths, and best use cases to find the ideal tool for your data projects.
