← all tracks

Python for AI

The everyday Python behind data and model code: dicts, nesting, text, caches and small parsers.

Beginner · 19 problems · 0 passed · Background reading: Python Engineering for AI — Overview

  1. 01Count Item Frequencieseasy
  2. 02Deduplicate List Preserving Ordereasy
  3. 03Invert a Dictionaryeasy
  4. 04Chunk a List into Batcheseasy
  5. 05Clean and Tokenize Texteasy
  6. 06Flatten an Arbitrarily Nested Listeasy
  7. 07Run-Length String Compressioneasy
  8. 08Safe Nested Dictionary Traversaleasy
  9. 09Flatten Nested Dictionary with Delimitersmedium
  10. 10Merge Overlapping Intervalsmedium
  11. 11Streaming Sliding Window Meanmedium
  12. 12LRU Cache Operation Simulatormedium
  13. 13Prefix Tree (Trie) Simulatormedium
  14. 14Token Bucket Rate Limiter Simulatormedium
  15. 15Levenshtein Edit Distance Metricmedium
  16. 16Time-To-Live (TTL) Cache Simulatorhard
  17. 17Package Build Order and Cycle Resolverhard
  18. 18Recursive Pure-Python JSON Serializerhard
  19. 19Abstract Syntax Tree (AST) Evaluatorhard

Next track: NumPy & Data Wrangling