This website contains years of content across multiple disciplines. It is my collection of insights, tutorials, and reflections across machine learning, data science, and professional development. Whether you're looking for technical deep dives, career guidance, or just curious about the intersection of AI and other disciplines, you've come to the right place.

Let me be your guide to the most valuable resources based on what you're looking to accomplish:

Choose Your Path:

• 🧠 Understand modern non-hype AI - Get clear explanations of cutting-edge research
• 💻 Level up your programming - Practical Python skills for real-world problems
• ⚡ Maximize productivity - Systems and tools to amplify your effectiveness
• 🔍 Build your career - Navigate the tech and research landscape successfully

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Who Am I?

I'm Jesper and you can use they/them pronouns for me. I earned my PhD in applied machine learning to geoscience from the Technical University of Denmark, where I focused on applications in geoscience resulting in several publications.

I love speaking at conferences, working on innovative projects, teaching, and creating content across multiple platforms:

• Blog articles that break down complex topics
• Books for deeper learning
• Weekly newsletter with curated insights
• YouTube tutorials and explanations

My work has been featured in respected publications and media outlets.

But enough about me, let's get you back into reading!

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🧭 Content Compass

Finding your Way Around

Regular Features

• Today I Learned: Short, practical insights from daily technical work.
• Deep Dives: Comprehensive explorations of single topics, published monthly.
• Projects: Real-world applications of machine learning and data science.

Reader Favourites

These articles have resonated most with readers and represent core themes of my work:

• 100 Tipps for Machine Learning — Practical advice for aspiring ML practitioners
• What I consider in a laptop for machine learning — Bridging the gap between hardware and AI
• Today I Learned about Cached_Property — Write cleaner code with cached properties
• A Life of Convergence and Divergence — Balancing learning and creation in modern tech
• My 10 favourite VSCode Extensions — Tools that vastly improve productivity

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🧠 Understand Modern AI

I translate complex machine learning research into accessible explanations with real-world context.

Explore the foundations and frontiers of AI through practical guides, technical breakdowns, and real-world applications. My articles range from beginner-friendly introductions to advanced implementation details.

What I Cover

Explore the foundations and frontiers of AI through practical guides, technical breakdowns, and real-world applications. My articles range from beginner-friendly introductions to advanced implementation details. I focus on demystifying AI concepts that often seem intimidating, breaking down:

• How algorithms actually work under the hood
• When and why to use specific techniques
• Ethical considerations and limitations
• Practical implementation details often missing from academic papers

Recent Posts

or try out this evergreen:

What is the Deepmind Nowcasting paper all about?

Popular Video Explanations

When text isn't enough, I create visual walkthroughs of complex concepts:

Topic Deep Dives

Browse all posts about machine learning or explore specific topics:

• Generative AI - Understanding diffusion models, transformers, and creative applications
• Deep Learning - Architecture design, training techniques, and performance optimization
• Natural Language Processing - From basic text analysis to advanced language models
• Computer Vision - Image recognition, object detection, and visual understanding systems
• Reinforcement Learning - Agents, environments, and decision-making algorithms

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💻 Level Up Your Programming

Solid programming skills form the foundation of effective data science work. Here are resources to sharpen your technical abilities:

What I Cover

Beyond algorithms and models, clean, maintainable code determines your long-term effectiveness. My programming content emphasizes:

• Writing readable, maintainable code that collaborators can understand
• Performance optimization techniques for data-intensive applications
• Software engineering best practices adapted for data science workflows
• Debugging strategies for complex computational problems

Latest Programming Resources:

Looking to improve your development environment? Check out these popular resources:

My 10 Favourite VS Code Extensions

Popular Video Explanations

How about some visual tips on Python and programming?

Topic Deep Dives

Browse all Python posts or explore specific programming topics:

• Data Structures - Beyond basics: specialized structures for data science
• Testing - Ensuring reliable code with proper test coverage
• Code Quality - Linting, formatting, and maintaining standards at scale
• Open Source - Contributing, maintaining, and collaborating on public projects
• Coding - General programming tips, tricks, and best practices

Real-World Examples

My programming content includes:

• Complete project walkthroughs with real codebases
• Before/after refactoring examples with performance metrics
• Common pitfalls and how to avoid them
• Transition strategies from notebooks to production systems

Community Resources

I maintain curated lists of:

• High-quality learning materials organized by skill level
• Code review checklists for data science projects
• Development environment configurations for various workflows
• Performance benchmarking tools and techniques

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⚡ Maximize Productivity

Learn systems and tools that multiply your effectiveness as a researcher, developer, or data scientist.

What I Cover

Productivity isn't just about doing more - it's about achieving meaningful results while maintaining balance. My approach focuses on:

• Building sustainable systems rather than relying on willpower
• Selecting and optimizing tools that reduce friction in your workflow
• Creating environments that support deep focus and creativity
• Balancing efficiency with effectiveness and well-being

Latest Productivity Insights:

or try out this evergreen:

Perfection is killing your productivity - Try this instead

Productivity Principles

My content is built around these core principles:

• Reduce Cognitive Load: Design systems that free your mental bandwidth
• Automate Repetitive Tasks: Identify and eliminate low-value work
• Create Effective Environments: Set up physical and digital spaces for optimal performance
• Implement Sustainable Habits: Build routines that compound over time

Popular Video Walkthroughs

See productivity systems in action:

Tools I Recommend:

My Productivity Tools

Topic Deep Dives

Browse all productivity posts or explore specific efficiency topics:

• Task Management - Beyond to-do lists: prioritization systems and workload balancing
• Digital Tools - Evaluations, configurations, and integration strategies
• Notion - Advanced setups, templates, and workflows for the popular tool
• VScode - Extensions, configurations, and productivity hacks for the code editor

Real-World Applications

My productivity content includes:

• Case studies from my own research and development work
• Before/after comparisons with concrete metrics
• Implementation guides for different contexts and constraints
• Troubleshooting common productivity system failures

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🔍 Build Your Career

Navigate the complex landscape of tech and research careers with practical advice and strategies.

What I Cover

A successful career in tech requires more than technical skills. My career content addresses:

• Strategic positioning in a rapidly evolving industry
• Building meaningful professional relationships
• Effectively showcasing your capabilities to decision-makers
• Navigating transitions between roles, industries, and specializations

Latest Career Insights:

or try out this evergreen:

How Do You Get Job Experience When No One is Hiring?

Navigating Common Challenges

• Overcoming imposter syndrome in technical roles
• Building visibility while maintaining authenticity
• Communicating complex work to non-technical stakeholders
• Balancing specialization with adaptability

Video Career Advice

Practical guidance for career development:

Topic Deep Dives

Browse all career-related posts or explore specific professional development topics:

• Job Searching - Strategic approaches beyond application volume
• Skill Development - Identifying and acquiring high-leverage capabilities
• Technical Interviews - Preparation frameworks and practice strategies

Industry Perspectives

My career content draws from experience across:

• Startups and established enterprises
• Research institutions and industry labs
• Traditional and hybrid organizations
• Different geographic markets and cultures

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Navigating This Site

Tags & Categories: Articles are organized by both broad categories and specific tags. Browse categories for thematic exploration or tags for targeted topics.

Search: Use the search function in the top menu to find specific concepts or technologies.

Chronology: The archives provide a historical view of all content, perfect for seeing how topics have evolved.

Stay Connected

The best way to keep up with new content and resources is through my newsletter:

Subscribe to receive insights from Late to the Party on machine learning, data science, and Python every Friday.

Follow Me Elsewhere:

• Bluesky, Threads, Mastodon for daily insights
• LinkedIn for professional updates
• GitHub for code examples
• YouTube for visual tutorials
• Tiktok for quick tips and personal insights

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Start Your Journey Today

Whether you're just beginning your machine learning journey or looking to refine advanced skills, I've created resources to help at every stage.

Pick a starting point that matches your current goals, and don't hesitate to reach out if you have questions or topic suggestions!

This site grows and evolves as I do. My hope is that you'll find something valuable here, whether you're a seasoned practitioner or just beginning your journey in data science and AI.

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