Outlier Detection: Introduction to Advanced Machine Learning (3)

Presented by WWCode Data Science 👩‍💻 Speaker: Rishika Singh, Joseph Itopa ✅ Topics: Outlier Detection, Types of Outliers, Dimensionality Reduction 📚 Slides: Download it at http://bit.ly/introtoadvml-week3-slides It has become quite common these days to hear people refer to modern machine learning systems as “black boxes” - data goes in, decisions come out, but the processes between input and output are disconnected. This 6-part technical series introduces some advanced machine learning concepts which encapsulate unsupervised machine learning problems and techniques with unstructured data like text and sequential datasets, focussing on understanding the math behind an algorithm and implementing it in Python. In this session, Joseph Itopa will introduce us to Outliers, their causes and how to handle them in your dataset and Rishika Singh will show us how to implement it in Python on real time datasets! 💬 Join our Slack channel for community support and more http://bit.ly/wwcodedatascience-joins... 🔗 Links to all our FREE events (and registration) and social media can be found at https://linktr.ee/wwcodedatascience 🎥 Check out recordings from other events from our track at https://linktr.ee/wwcodedatascience_r... ___ Learn more about Women Who Code: 💻 WWCode Digital Events: https://www.womenwhocode.com/digital 📫 Weekly Newsletter: https://bit.ly/2LxTMps 💼 Job-Only Newsletter: https://bit.ly/3cvz70W 🙋🏾‍♀️ Events-Only Newsletter: https://bit.ly/2LBvlHn 🖥 Coding Resources: https://www.womenwhocode.com/resources 🔎 Job Board: https://www.womenwhocode.com/jobs 💌 Make a Donation: https://www.womenwhocode.com/donate