• Go
• Typescript
• Logic
• Tensorflow
• Various math concepts (thanks to project Euler)
• Neuroscience
• Automata theory
• Self-reproducing automata
• Cognitive science

Every year I learn new things. In the articles listed below I record the various things I've learned over the years.

• 2014
• 2015
• 2016
• 2017
• 2018
• 2019
• 2020
• 2021
• 2022

• Composer (proxy + client)
• Anatomy
• Webpage crawling
• Chrome api
• pico
• anki server protocol
• Semantic versioning
  • building a phar
  • php parsing
  • releasing php open source software
• laravel
• cordova
  • ionic framework
• nodejs
  • debugging
  • profiling

• A/B testing
• Continuous experimentation
• Kubernetes
• Helm
• GCP
  • Kubernetes Engine
  • BigQuery
  • Dataflow
  • Kubeflow
  • Airflow/Composer
  • VPC/Network/Firewall/Cloud armor
  • Cloud profiling
• Go
• GRPC
• Terraform
• Prometheus
  • Alerts
  • Recording rules
• Grafana
• Datadog
• Kafka
• Load balancing
  • GRPC
  • Kafka
• Lens (GUI for Kubernetes)

In this article I define a 1-5 rating scale for books in order to be consistent across my evaluations. Given that rating books is somewhat subjective, introducing some amount of standardization on how I rate them should help with managing my reading.

Format of presentation:

Score (from 1 to 5) Representative emoji

• Satisfaction
• Words expressing the level of satisfaction
• Strength of recommendation

1 🤮

• unsatisfactory
• very bad, horrible, boring, repetitive, disagreeable to read, waste of time, can't force myself to read
• strongly not recommended

2 ☹️

• unsatisfactory
• bad
• not recommended

3 😐

• satisfactory
• neutral
• might want to read

4 ☺️

• satisfactory
• good
• recommended

5 😍

• satisfactory
• very good, great, amazing, exciting, intriguing, fascinating, full of new knowledge, can't stop reading
• strongly recommended

References

• https://readingbookslikeaboss.com/review-rating-scale/
• https://www.writoscope.com/reading/how-rate-book-rating-system/