ML Experts - Sasha Luccioni

🚀 If you're interested in learning how ML Experts, like Sasha, can help accelerate your ML roadmap visit: https://bit.ly/3FcyWXI to learn more. Sasha is a Research Scientist at Hugging Face where she works on creating ethical data and model development practices, developing tools and frameworks for data-centric AI practice, and contributing to democratizing AI and Machine Learning for all. In this video you'll hear Sasha talk about: - 🕤 Timestamps 0:00 Intro 1:38 Sasha Luccioni’s background 3:22 What Sasha’s excited to work on 5:15 Carbon footprint of an email (among other things) 6:23 Environmental impact of tech/AI 7:00 Measuring emissions 7:56 Computing region (cloud instances) emission 8:28 Energy grids 9:48 Nudge theory 10:55 How ML teams & engineers can become more aware of their environmental impact 12:22 Tackling climate change with machine learning 12:50 Renewable energy + time series prediction 14:25 Detecting deforestation & wildfires 15:43 Cost + benefit of environmental efforts (climatechange.ai) 17:40 Common mistakes do you see ML Engineers/Teams make? 19:06 How ML models fail to get in front of the right people 22:17 The importance of meaning 25:32 The importance of ML accessibility & democratization 27:46 Attaining data (jungle camera example) 31:36 Tips for ML teams/engineers lacking necessary data 32:15 Soup kitchen dataset example 34:40 Community involvement 35:26 What industries are you most excited to see ML be applied? 37:13 If you could go back and do one thing differently at the start of your ML career, what would it be? 38:44 Mathematics - how much do you need to know? 40:51 Best advice for someone looking to get into AI/ML? 42:37 Classifying butterflies 45:06 Will AI take over the world? 47:22 Gardening 49:00 The value of tangible projects 49:24 Favorite Machine learning papers? 51:35 Model evaluation 53:36 Where you can follow Sasha online 🔗 Honorable mentions + links: Tackling Climate Change with Machine Learning: https://dl.ac