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Join now and get tips and tricks directly in your inbox. ๐Ÿ“ฌ Learn how to build ML systems end-to-end. ๐Ÿš€

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Build ML Systems End-to-End

Design ยท Develop ยท Deploy ยท Iterate

Find everything you need to know about building machine learning systems end-to-end. Get expert insights on how to design, develop, deploy and iterate on ML-powered software applications.

1. โš™๏ธ Setup

  • Environment

2. ๐Ÿ—ƒ๏ธ Data

  • Preparation
  • Exploration
  • Preprocessing

3. ๐Ÿค– Model

  • Training
  • Tuning
  • Evaluation
  • Serving

4. ๐Ÿ“ฆ Utilities

  • Logging
  • Documentation
  • Style Guides

5. ๐Ÿ‘ฉโ€๐Ÿ”ฌ Testing

  • Code
  • Data
  • Models

6. โ™ป๏ธ Reproducibility

  • Versioning

7. ๐Ÿš€ MLOps

  • Automation
  • CI/CD
  • Monitoring
  • Version Control

Info

The articles are currently under development and will be frequently refreshed with new updates. Keep an eye out! ๐Ÿš€
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Who is this blog for?

๐Ÿ‘จ๐Ÿผโ€๐Ÿ’ป Developers ๐Ÿง‘โ€๐Ÿ”ฌ Data Scientists ๐Ÿ‘จโ€๐Ÿ”ง ML Engineers

This blog is tailored for anyone interested in mastering the art of deploying robust, scalable, and efficient machine learning solutions. From foundational concepts to advanced techniques, we will cover a wide range of topics that cater to the needs of developers, data scientists, and ML engineers alike.

๐Ÿ‘จ๐Ÿผโ€๐Ÿ’ป Developers

Whether you're a seasoned software engineer or a junior developer, the content will help you bridge the gap between traditional software development and machine learning.

๐Ÿง‘โ€๐Ÿ”ฌ Data Scientists

If you're passionate about data analysis, predictive modeling, and statistical inference, the blog will provide you with the tools and techniques to bring your models to life in real-world applications.

๐Ÿ‘จโ€๐Ÿ”ง ML Engineers

For those specializing in machine learning engineering, our content will offer valuable insights into best practices for deploying, monitoring, and maintaining ML systems in production environments.


Meet the author

Photo of Author

Hi, I'm Nikola Dakiฤ‡

I have a bachelor's degree in Software Engineering and a master's in Intelligent Systems. I'm currently a Senior Software Engineer at SugarCRM, where I'm responsible for overseeing the entire lifecycle of machine learning projects. Throughout my career, I've been part of several ML projects, working on predictive modeling, computer vision, and large language models (LLM).
My passion for building end-to-end software applications has given me solid experience in software engineering, machine learning, and DevOps. I'm thrilled to share my expertise with you, so you can create machine learning systems that are robust, scalable, and efficient.


What you can expect to learn?

๐Ÿ“ Foundational Concepts

Understand the underlying theories and methodologies that form the backbone of both machine learning and software engineering.

๐Ÿ’ป Practical Tutorials

Step-by-step guides to building ML-powered software applications from scratch. From data preprocessing to model training, deployment, and beyond.

๐Ÿš€ Deployment Strategies

Learn about the various deployment strategies for production ML applications, including containerization, serverless architecture, and cloud-based solutions.