AI News, NIPS Proceedingsβ

NIPS Proceedingsβ

Part of: Advances in Neural Information Processing Systems 27 (NIPS 2014) Gaussian processes (GPs) are a powerful tool for probabilistic inference over functions.

They have been applied to both regression and non-linear dimensionality reduction, and offer desirable properties such as uncertainty estimates, robustness to over-fitting, and principled ways for tuning hyper-parameters.

We show that GP performance improves with increasing amounts of data in regression (on flight data with 2 million records) and latent variable modelling (on MNIST).

Introduction to Data Science with R - Data Analysis Part 1

Part 1 in a in-depth hands-on tutorial introducing the viewer to Data Science with R programming. The video provides end-to-end data science training, including ...

Social Data Processing using Exchangeable Models

Social Data Processing using Exchangeable Models: Recommendation Systems, Crowd-sourcing, and Graphon Estimation Much of modern data is generated ...

Serving Models in Production with TensorFlow Serving (TensorFlow Dev Summit 2017)

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11. Introduction to Machine Learning

MIT 6.0002 Introduction to Computational Thinking and Data Science, Fall 2016 View the complete course: Instructor: Eric Grimson ..

Lecture 3 | Loss Functions and Optimization

Lecture 3 continues our discussion of linear classifiers. We introduce the idea of a loss function to quantify our unhappiness with a model's predictions, and ...

Deploying and Scoring Models In-Database with SAS® Scoring Accelerator for Teradata

Learn how to score the models in-database using SAS® Scoring Accelerator for Teradata and Hadoop – deploying models more efficiently and effectively.

Data Modeling and Inference Overview

Dr. Rafael Irizarry from Harvard University presents a lecture titled "Data Modeling and Inference." View slides Coming soon... Lecture Abstract This lecture will ...

Python Computer Vision -- Inference Tensorflow #3

This is a continuation of Transfer Learning With Tensorflow #1,2 Please watch those videos before watching this one: ...

Torsten Scholak, Diego Maniloff Intro to Bayesian Machine Learning with PyMC3 and Edward

"Speakers: Torsten Scholak, Diego Maniloff There has been uprising of probabilistic programming and Bayesian statistics. These techniques are tremendously ...

Probability Theory - The Math of Intelligence #6

Only a few days left to signup for my Decentralized Applications course! We'll build a Spam Detector using a machine learning model ..