Geek Reading: Machine Learning, Advanced Algorithms, and More
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Join For FreeToday we have some very good AI/ML posts. First, Pete Warden tells us how to break into machine learning. It is some very practical advice on how to get started. Machine Learning Mastery, my new favorite ML blog, talks about boosting and AdaBoost. David Lettier shows us how to develop K-Means from scratch. Lastly, on An Uncommon Lab we get to see how Kalman Filters work.
As always, enjoy today’s items, and please participate in the discussions on these sites.
Startups, Career, and Process
- Why You Should Do Periodic Reviews of Legacy Code | DaedTech
- Updating your outdated knowledge by moving to a new web stack | Cindy Potvin
Design and Development
- Functors, Applicatives, and Monads in Plain English | Russ Bishop
- When to Rewrite from Scratch – Autopsy of a Failed Software | Code Ahoy
- Windows Subsystem for Linux Overview | MSDN
- Simple Everyday Tips for Vaadin Developers – Part 2: Using CDI | DZone Java
- Bots won’t replace apps. Better apps will replace apps. | Dan Grover
- you can take the derivative of a regular expression?! | Julia Evans
Concurrency, Performance, and Scalability
- Fast incremental sort | Lars Hagen
AI, Machine Learning, Research, and Advanced Algorithms
- How to break into machine learning | Pete Warden
- When Does Deep Learning Work Better Than SVMs or Random Forests? | KD Nuggets
- Deep Learning for Named Entity Recognition | Deep Learning Kit
- Boosting and AdaBoost for Machine Learning | Machine Learning Mastery
- Pride and Prejudice and Z-scores | Revolution Analytics
- K-Means from Scratch | David Lettier
- How Kalman Filters Work, Part 1 | An Uncommon Lab
Infrastructure, Operations, and DevOps
- Continuous Deployment With Helm, Deis Workflow, and Wercker | Deis
- Count me as a systemd convert | The Changelog
- The Joy of Deploying Apache Storm on Docker Swarm | High Scalability
Security, Encryption, and Cryptography
- Possible Jenkins Project Infrastructure Compromise | Jenkins
- ELF Shared Library Injection Forensics | Backtrace I/O
Link Collections
- Some links on Java garbage collection | Julia Evans
- Programming Digest #156 for April 25, 2016 | Weekly Programming Newsletter
- Dew Drop – April 25, 2016 (#2237) | Morning Dew
Topics:
code review,
functors,
deep learning,
machine learning,
apache,
docker swarm
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