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Articles on building things — cloud platforms, AI agents, data pipelines, mobile apps, and the occasional robotic arm.
55 ARTICLES · 2012 — 2026 · PAGE 4 OF 6
2021 1 posts November 26, 2021
on Translucent Computing Workflow Engine -- Data Pipeline Explains foundational workflow and data pipeline concepts including DAGs, and introduces Apache Airflow as a mature workflow manager for cloud-native environments.
2020 8 posts November 26, 2020
on Translucent Computing What is Kubernetes, and Why are My Cloud Costs So High?! -- Part 1 Demystifying Kubernetes and understanding why cloud costs spiral when running containerized workloads without proper resource management.
January 16, 2020
on Translucent Computing Text-To-Speech Example Demonstrates audio generation for blog content using text-to-speech technology with Python and Jupyter Notebook.
January 10, 2020
on Translucent Computing Bimodal Helm Charts Explores bimodal IT management approaches applied to Helm chart configurations for Kubernetes deployments.
January 6, 2020
on Translucent Computing Performance Waveform Generator Starter Notebook Starter notebook demonstrating sine wave generation with noise, using pandas for data processing and spectrogram visualization in Python.
January 6, 2020
on Translucent Computing Using SymPy to Build ECG Model Applies computational mathematics using SymPy for symbolic, numerical, and graphical approaches to building an ECG model.
January 6, 2020
on Translucent Computing SymPy and ECG Notebook Companion Jupyter notebook for the SymPy ECG model post, providing runnable code for electrocardiogram modeling.
January 2, 2020
on Translucent Computing Optimizing code with pandas and NumPy Discusses SciPy framework optimization techniques for data science using pandas and NumPy for improved performance.
January 2, 2020
on Translucent Computing Pandas and NumPy Performance Test Notebook Testing notebook demonstrating how to optimize Python code with pandas and NumPy for improved computational efficiency.
2019 1 posts December 31, 2019
on Translucent Computing Performance In Jupyter Python Examines Jupyter magic commands for systematically identifying and resolving performance bottlenecks in Python code.
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