Discover the world of distributed systems and build your own Python RPC server using Flask. Harness the power of remote procedure calls today!

Get Started with RPC - A Beginner's Guide to Building a Python RPC Server Using xmlrpc and jsonrpc.

Learn how to verify your backups with Restic, ensure completeness, integrity, and recoverability. Automate the process for peace of mind. Read now

Learn the difference between imperative & grammar of graphics approach to plotting. Imprerative approach is simple and easy to understand, but grammar of graphics approach is more advanced and efficient. Examples with matplotlib and plotly express included.

Discover the future of MLOps specializations, including Explainable AI/MLOps, Federated Learning/Edge MLOps, Reinforcement Learning/MLOps, AI/ML in IoT and IIoT, Model Explainability and Fairness.

The most widely used libraries for plotting in python are matplotlib, Plotly, seaborn, and bokeh. This article describes 10 other powerful plotting libraries available in Python that can be used to create high-quality plots and visualizations.

This post presents the trend-classifier package that can be used for signal segmentation into parts where the trend is coherent.

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A great Pelican theme can make all the difference. Learn how to design your own with our comprehensive tutorial.

This post describes techniques that help to get most accurate suggestions from the GitHub Copilot "Your AI pair programmer". For those who never heard of Copilot there is short introduction, if you already know Copilot - you can jump directly to section 4: "How to get most of GitHub Copilot".

Learn how to set up VSCode as a Nim IDE from scratch. Includes instructions for downloading VSCode, installing the Nim extension, configuring settings, and debugging Nim code.

This post proposes a 4-step path for learning Bayesian methods. The first step is going through the book: "Bayesian methods for hackers", second, using complementary books for probability and statistics, the third, reading How to become a Bayesian in eight easy steps: and last, going through the book full of exercises: "Think Bayes".

Guide on how to install TensorFlow cpu-only version - the case for machines without GPU supporting CUDA. Step-by-step procedure starting from creating conda environment till testing if TensorFlow and Keras Works.

Having several notebook-based projects behind you might result in a mess in the projects directory. Organize your Data Science project based on Jupyter notebooks in a way that one can navigate through it. Especially that "the one" will be most probably you in a few months time. To achieve that: keep your projects directory clean, name the project in a descriptive way and take care of the internal structure of the project.