DS Unit 4 Sprint 13

Course Overview

Welcome to DS Unit 4, Sprint 13. This sprint focuses on Natural Language Processing (NLP), covering text tokenization, vector representations, document classification, and topic modeling.

Course Objectives

  • Learn to tokenize text and preprocess natural language data
  • Create vector representations of documents for similarity calculations
  • Build document classification pipelines using NLP techniques
  • Implement topic modeling using the Latent Dirichlet Allocation process
  • Apply natural language processing to real-world data

Sprint 13 Study Guide

How to Pass This Sprint

  • Receive a 100% on the Sprint Challenge
    • A Sprint Challenge is a time-bound project that you must complete using the skills you've learned in each Sprint.
    • After you make your first attempt at a Sprint Challenge, you will have unlimited attempts to get a passing grade of 100%.
  • Receive 80% on the Sprint Assessment
    • A Sprint Assessment is a multiple-choice test that checks for understanding of the knowledge you've gained throughout the Sprint.
    • After you make your first attempt at a Sprint Assessment, you will have unlimited attempts to get a passing grade of 80%.

Module Resources