Introduction to Machine Learning in Python with Scikit-Learn

Channel:
Microsoft Research
Subscribers:
342,000
Published on ● Video Link: https://www.youtube.com/watch?v=6nSzSOo_11I


Duration: 1:16:19
5,243 views
29

This talk will introduce scikit-learn, an Open Source project for Machine Learning in Python and review some new features from the recent 0.15 release: faster randomized ensemble of decision trees and optimization for the memory usage when working on multiple cores. Finally we will demo the typical usage of scikit-learn for interactive predictive analytics in combination with other open source projects from the Python ecosystem namely: numpy, matplotlib, pandas and IPython notebook.



Other Videos By Microsoft Research


2016-06-21Code Hunt Workshop - Day 2 Session 4B
2016-06-21Code Hunt Workshop - Day 1 Session 3
2016-06-21The Laws of Programming with Concurrency
2016-06-21Designing Technology for Mental Health and Wellbeing
2016-06-21DNN-Based Online Speech Enhancement Using Multitask Learning and Suppression Rule Estimation
2016-06-21Computing Reliably with Molecular Walkers
2016-06-21Challenges in automated verification and synthesis for molecular programming
2016-06-21Decompositions of Natural Signals Still Need Fresh Ideas
2016-06-21Provable Non-convex Projections for High-dimensional Learning Problems -Part2
2016-06-21Optimal Design for Social Learning
2016-06-21Introduction to Machine Learning in Python with Scikit-Learn
2016-06-21Lab tutorial: Learning about Shape
2016-06-21Improving Behavioral Health Intervention Technologies: Harnessing the Human Side of Apps
2016-06-21Charles River Crypto Day - The Power of Negations in Cryptography
2016-06-21Scalable Kernel Methods via Doubly Stochastic Gradients
2016-06-21Molecular Tumor Boards: What they are; What they do; What they need
2016-06-21The Contextual Bandits Problem: A New, Fast, and Simple Algorithm
2016-06-21Cell cycle switching by an algorithm
2016-06-21Provable Non-convex Projections for High-dimensional Learning Problems - Part1
2016-06-21Northwest Probability Seminar 2014 - Sampling from the Fomin-Kirillov distribution
2016-06-21Computer Vision - StAR Lecture Series: Object Recognition


Tags:
microsoft research
machine learning
deep neural networks