To learn more about data structures and algorithms I will be completing the following guided project tutorial:
- Using a Python script to randomly generate words from a dictionary.
- Building sentences by sampling these words using a Markov language model.
- Implementing grammar rules parsed from the text of a large document set.
- Building data structures including linked lists, hash tables, stacks, queues, and heaps to store the words and sentences.
- Analyzing the inner workings and performance tradeoffs of each data structure.
- Deploying your language model to a Flask web server on Heroku and connect it to Twitter to let users tweet their favorite results.
- Find data sources such as books, articles that you want to use for your Tweeta Generator
- Page 1: Let's Get Started
- Develop Where To Go From Here Challenges
- Page 2: Random Dictionary Words
- Develop Bonus challenges
- Check out Python resources
- Page 3: Analyze Word Frequency in Text
- Design, code and ship stretch challenges
- Check out Resources
- Page 4: Stochastic Sampling
- Develop stretch challenges
- Check out resources
- Page 5: Flask Web App
- Develop stretch challenges
- Check out resources
- Page 6: Application Architecture
- Design, code, and ship stretch challenges
- Page 7: Generating Sentences
- Develop stretch challenges
- Check out resources
- Page 8: Linked List
- Develop stretch challenges
- Check out Hash Table resources
- Page 9: Hash Table
- Design, code, and ship stretch challenges
- Check out Algorithm Analysis Resources
- Annotate a LinkedList class and a HashTable class
- Stretch Challenges Page 10: Performance Analysis
- Check out Higher Order Markov Chains
- Page 11: Markov Chains Revisited & Page 12: Creating a Corpus
- Develop Page 11: Markov Chains Revisited stretch challenges
- Check out Regular Expressions resources
- Page 13: Parsing Text and Clean Up & Page 14: Tokenization
- Design, code, and ship stretch challenges for Page 13 & 14
- Prepare, review, study for Written Assessment (Final Exam)