Python代做 | Email Classification using Machine Learning


Project Proposal Team Accenture Fall 2019
The Capstone Experience Page 1 of 2 Michigan State University
Team Name: Accenture
Project Title: Email Classification using Machine Learning
Project Description:
According to SpamHause, spam emails account for almost 45% of emails sent, to give some numerical
perspective on what we are dealing with it is estimated that about 15 billion spam and phishing emails
are sent every single day! Despite increased employee training, and frequent high-profile data breaches
in the news, many employees continue to view their email and devices as inherently secure. It’s no secret
that most data breaches originate with end-users and given the rise in social engineering, SPAM-based
phishing attacks, and malware laced messages, it is becoming an ever-growing challenge for companies
to classify and detect emails that may lead to an infection or a security breach.
Accenture Security employed a Machine Learning approach to classify and categorize the incoming emails
with natural language processing and artificial intelligence. We would like to create and enhance
classification and clustering models to help triage incoming emails into following categories:
a) Email with malicious attachments
b) Email with URL that leads to a payload
c) Email that leads to credential phishing
d) Non-interesting emails (pharma, dating, advertising, and other illicit types)
e) Etc.
Required Technologies:
• Python
• Tesnorflow
• MangoDB
• Bootstrap front-end framework
• Elas
Suggested Resources:
• Accenture | Artificial Intelligence (AI) | What it is & Why it Matters |
• Accenture | Artificial Intelligence (AI) | Artificial Intelligence (AI) Services & Solutions
• A free online introduction to artificial intelligence for non-experts |
• Tensorflow courses |


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