Explore the realities of machine learning careers in this insightful ACM-W panel discussion featuring successful ML professionals. Gain practical guidance on identifying suitable ML problems, determining solution success, transitioning from coursework to real-world applications, and navigating the evolving ML landscape. Learn from experts in academia and industry as they share their experiences, debunk common myths, and offer valuable advice for aspiring ML professionals. Discover the importance of data emphasis, feature development, and problem selection in ML projects. Understand the challenges and opportunities in the field, including the gap between hype and reality. Acquire essential skills, networking strategies, and career development tips to thrive in the dynamic world of machine learning.
Celebrating Technology Leaders - Machine Learning Careers: Looking Beyond the Hype
Association for Computing Machinery (ACM) via YouTube
Overview
Syllabus
Introduction
Question
Nehas Story
PhD Myth
Hype vs Reality
Learning is not magic
Emphasizing data
Types of problems for ML
When to pick a good problem
Translating common sense into features
Industrial perspective
Chatbots
Opportunities and Challenges
Challenges
Challenges from academia
Opportunities
Audience Questions
Know Your Value
Have a Network Mindset
Improve Your Strengths
Audience Question
Making Tough Decisions
Bring Everyone Along
Take Responsibility
Netflix
Principles of Parsimony
Developing Features
Conferences
LinkedIn
Network
Github
Audience Feedback
Advice for Students
What Skills Do You Need
Final Thoughts
Advice
Final Advice
Keyword
Taught by
Association for Computing Machinery (ACM)
