Nathan Epstein - Using Random Forests in Python скачать в хорошем качестве

Nathan Epstein - Using Random Forests in Python

Filmed at PyData London 2017 Description This talk will be an exposition of machine learning with random forests for Python programmers. The talk will cover the internals of how random forests are implemented, applications that are well suited to the use of random forests, and Python code samples to demonstrate their use. Abstract Outline Intro (5 minutes) What are random forests, how are they used, and what Python software is available for using them? What strengths do they have relative to other models (scalability and applicability to a broad range of problems)? Forest Internals (15 minutes) Decision Trees (5 minutes) Presentation of the decision tree model, the building block of random forests. Entropy Minimization (5 minutes) Explanation of how decision trees are tuned using entropy minimization. Building Forests from Decision Trees (5 minutes) Explanation of how decision trees are aggregated to form random forests. Illustrative Examples (10 minutes) Regression on non-linear functions (5 minutes) Classification with unscaled features (5 minutes) www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. We aim to be an accessible, community-driven conference, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases. 00:00 Welcome! 00:10 Help us add time stamps or captions to this video! See the description for details. Want to help add timestamps to our YouTube videos to help with discoverability? Find out more here: https://github.com/numfocus/YouTubeVi...