Jiří Neoral se věnuje praktické přípravě na certifikace Microsoft Fabric DP-600 a DP-700. Na svém blogu sdílí strategie, tipy a zkušenosti s přípravou na zkoušky, práce s pipelines, notebooks, KQL a dalšími nástroji platformy Fabric.
Andrew Healey writes about programming languages, compiler design, systems programming, and performance optimization. His blog covers building interpreters, compilers, sandboxes, games, and creative developer tooling, often with a focus on speed and efficiency.
Tigran Hakobyan writes about software development, AI-enhanced engineering, and career growth in tech. His blog covers programming trends, CI/CD practices, reliability, and personal reflections on building a career while balancing life.
Rajeev Singh is an AI and Gen AI expert focusing on multi-agent systems, Microsoft Agent Framework, and Azure AI services. His blog covers AI agent development, enterprise chat AI, and advanced serverless AI solutions with practical implementation guides.
Will Kurt is a data scientist and author writing about probability and statistics through his blog Count Bayesie. He explores Bayesian and frequentist methods with an intuitive, insight-driven approach, making complex ideas in probability accessible and engaging.
Dan Simpson is a technical writer and researcher focusing on C++, JAX, and advanced statistical computing. His blog dives deep into sparse matrices, autodiff, Bayesian methods, and modern AI techniques, blending theory with practical, hands-on implementations.
Marc Brandner is a software engineer and technical writer covering Kubernetes, Docker, Linux, and data visualization. His articles explore cloud-native tooling, container workflows, Python utilities, and practical guides for developers and DevOps engineers.
Rajesh P writes about building scalable, secure, and high-performance backend systems. His articles cover Spring Boot, API design and versioning, system design fundamentals, and modern GenAI concepts like rerankers, LLM limits, and latency optimization.
Michael Toth is a consulting data scientist and writer known for clear, practical guides to data visualization in R. His work focuses on ggplot, effective graph design, and helping data scientists communicate insights with impact.
Yuxin Wu shares in-depth insights on Python, PyTorch, and large-scale software design. Explore tutorials on memory optimization, data loading, stacked diffs, static initialization, and building efficient deep learning systems.
Unmesh Gundecha shares insights on AI-assisted programming, test automation, and software architecture. Explore tutorials on Docker, Kubernetes, command-line tools, and practical coding projects.
Mavrick Laakso shares practical guides on CI/CD, AWS cloud, Ruby on Rails, and iOS testing. Explore tutorials on GitHub Actions, Terraform, Lambda optimization, and building scalable, cost-effective cloud solutions.
Patrick Coakley provides tutorials and insights on C++, C#, .NET, Python, and game development with Godot. Learn programming fundamentals, design patterns, CLI tools, and practical software development tips for beginners and pros alike.
Alan Richardson is a software testing expert focused on exploratory testing, web testing, and test automation. He shares practical tutorials, tools, and podcasts covering WebDriver, browser testing, and the real-world use of AI in testing.
Avi Singh writes about computer vision, deep learning, and robotics, with hands-on tutorials and research-driven insights. His work covers visual odometry, activity recognition, neural networks, and practical implementations using OpenCV, CUDA, and MATLAB.
Miguel Grinberg is a software engineer and Python expert known for in-depth articles on Flask, web security, Python performance, and backend development. He shares practical tutorials, benchmarks, and insights drawn from real-world open-source and framework work.
Vincent Warmerdam is a data scientist and Python educator known for exploring practical data tools, developer workflows, and thoughtful software design. He regularly writes about Python, machine learning, tooling experiments, and lessons learned from real-world data work.
Mark Saroufim is a software engineer and writer focused on machine learning systems, PyTorch, reinforcement learning, and the intersection of computation, mathematics, and product thinking. His writing blends hands-on engineering with theory, exploring everything from deep learning infrastructure to philosophy of computation.
P. Galeone is a software engineer and writer focused on cloud infrastructure, AI systems, and technological sovereignty. His work explores practical implementations in Go and Python, AI-driven automation, and the societal implications of dependence on foreign cloud and digital platforms.
Sebastian Witowski is an independent Python consultant, freelancer, and international speaker based in Poland. With 10+ years of experience—including work at CERN—he specializes in Python development for finance and energy trading, covering web development, ETL pipelines, and technical workshops.
