Naive Bayes 101: Resume Selection with Machine Learning
Create a pipeline to remove stop-words, punctuation, and perform tokenization
Understand the theory and intuition behind Naive Bayes classifiers
Train a Naive Bayes Classifier and assess its performance
In this project, we will build a Naïve Bayes Classifier to predict whether a given resume text is flagged or not. Our training data consist of 125 resumes with 33 flagged resumes and 92 non flagged resumes. This project could be practically used to screen resumes in companies.
您要培养的技能
- Data Cleansing
- Machine Learning
- NLP
- Artificial Intelligence(AI)
- Computer Science
分步进行学习
在与您的工作区一起在分屏中播放的视频中，您的授课教师将指导您完成每个步骤：
Task 1: Understand the Problem Statement and Business Case
Task 2: Import libraries and datasets
Task 3: Perform exploratory data analysis
Task 4: Perform data cleaning
Task 5: Visualize cleaned datasets
Task 6: Prepare the data by applying count vectorization
Task 7: Understand the intuition behind Naive Bayes Classifier - Part #1
Task 8: Understand the intuition behind Naive Bayes Classifier - Part #2
Task 9: Train a Naive Bayes classifier model
Task 10: Assess trained model performance
指导项目工作原理
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在分屏视频中，您的授课教师会为您提供分步指导
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