'Deep learning' presentation slideshows

Deep Learning from Speech Analysis/Recognition to Language/Multimodal Processing

Deep Learning from Speech Analysis/Recognition to Language/Multimodal Processing. Li Deng Deep Learning Technology Center, Microsoft Research, Redmond, WA. USA A Tutorial at Intern. Workshop on Mathematical Issues in Information Sciences (MIIS). Outline.

1.65k views • 125 slides

Data Mining Practical Machine Learning Tools and Techniques Slides for Chapter 10, Deep learning

Data Mining Practical Machine Learning Tools and Techniques Slides for Chapter 10, Deep learning of Data Mining by I. H. Witten, E. Frank, M. A. Hall, and C. J. Pal. Introducing Deep Learning.

1.46k views • 123 slides

Backtracking search: look-back

Backtracking search: look-back. ICS 275 Spring 2009. Look-back: Backjumping / Learning. Backjumping: In deadends, go back to the most recent culprit. Learning: constraint-recording, no-good recording . good-recording. Backjumping. (X1=r,x2=b,x3=b,x4=b,x5=g,x6=r,x7={r,b})

759 views • 60 slides

Colorado MGMA Conference, September 13, 2019

Artificial Intelligence (AI) & Machine Learning (ML): Challenges and Opportunities for Health Care Kent Bottles, MD. Colorado MGMA Conference, September 13, 2019. The Four Industrial Revolutions. First (1760 to 1840): the steam engine

740 views • 54 slides

Lecture 1: Deep Neural Networks and Backpropagation Training

Lecture 1: Deep Neural Networks and Backpropagation Training. Reading and Research in Deep Learning James K Baker. 11-364 Deep Learning R&R. Major Project. Read to get the gist. Hands-on Tutorial Books with Sample Code. Background Tasks. Leading Edge Research Papers.

1.01k views • 54 slides

Spilling the Beans

Spilling the Beans. Joint Convention 2009 Presented by: John Swanson, TIE. secrets which are hard to grasp in their deep meaning and difficult to act on in combination. the secret to a long life. the secret to a long and loving marriage.

692 views • 54 slides

What is Scientific Machine Learning?

What is Scientific Machine Learning?. Chris Rackauckas Massachusetts Institute of Technology, Department of Mathematics University of Maryland, Baltimore, School of Pharmacy, Center for Translational Medicine. Scientific ML/AI is Domain Models with Integrated Machine Learning.

1.05k views • 45 slides

Deep Learning on Hadoop

Deep Learning on Hadoop. Scale out Deep Learning on YARN. Adam Gibson. Email : 0@blix.io Twitter @ agibsonccc Github github.com/agibsonccc. Slideshare slideshare.net / agibsonccc Teaching zipfianacademy.com Press wired.com /2014/06/skymind-deep- learning. Josh Patterson. Email:

731 views • 37 slides

Prediction of Information Cascades via Content and Structure Integrated Whole Graph Embedding

BSMDMA Workshop @ IJCAI 2019. Prediction of Information Cascades via Content and Structure Integrated Whole Graph Embedding. Feng Xiaodong ? Zhao Qihang , Liu Zhen Speaker: Feng Xiaodong From: University of Electronic Science and Technology of China. 2019-8-11 Macao, China. CONTENT.

529 views • 29 slides

Calibrating Uncertainties in Deep Learning Models at Scale

Calibrating Uncertainties in Deep Learning Models at Scale. Research Challenges and Opportunities at the Interface of Machine Learning and Uncertainty Quantification July 25, 2019. Gemma J. Anderson , Jim A. Gaffney, Sam A. Jacobs, Brian Van Essen and Brian K. Spears. UQ.

393 views • 29 slides

Computer Vision since Deep Learning

504 views • 29 slides

CSC 578 Neural Networks and Deep Learning

CSC 578 Neural Networks and Deep Learning. 5. TensorFlow and Keras (Some examples adapted from Jeff Heaton , T81-558: Applications of Deep Neural Networks ). Intro to TensorFlow and Keras. Hyperparameters (1) Activation (2) Loss function (3) Optimizer (4) Regularizer

844 views • 21 slides

Solikin solikin @ binainsani . ac.id Dir. Eksekutif APTIKOM/Ketua STMIK Bina Insani

I NOVASI & GARTNER HYPE CY C LE. Solikin solikin @ binainsani . ac.id Dir. Eksekutif APTIKOM/Ketua STMIK Bina Insani Minggu, 25 Februari 2018, Hotel Grand Asrilia Bandung. Insert LOGO. Seminar Nasional, STMIK Rosma Karawang. AGENDA. Gartner Hype Cycle For Emerging Technologies 2017

506 views • 21 slides

Woojae Kim 1 , Jongyoo Kim 2 , Sewoong Ahn 1 ,Jinwoo Kim 1 , and Sanghoon Lee 1

Deep Video Quality Assessor: From Spatio-temporal Visual Sensitivity to A convolutional Neural Aggregation Network. Woojae Kim 1 , Jongyoo Kim 2 , Sewoong Ahn 1 ,Jinwoo Kim 1 , and Sanghoon Lee 1 1 Department of Electrical and Electronic Engineering, Yonsei University

368 views • 21 slides

Comprehensive Approach to Leadership Development in the Ottawa Catholic School Board

Comprehensive Approach to Leadership Development in the Ottawa Catholic School Board. OCSB Case Study https://goo.gl/ahXiKv. 67 elementary schools. 2900 square kilometers. 2 intermediate schools. 15 intermediate/secondary schools. 4000 Staff. 40, 000 Students. Building.

419 views • 19 slides

Medical Informatics and Explainable AI

Medical Informatics and Explainable AI. CERN openlab Summer Student Lectures. 23/07/2019. Taghi Aliyev. Outline. What do we mean with Medical Informatics? Areas of application Outstanding issues and open questions: Explainable AI, Trustability Data Set generation and curation

436 views • 15 slides

INTRODUCTION

296 views • 14 slides

Week 2

Week 2. Jila Naeini (2018). Deep Learning An attempt to define a new desired outcome of the education system.

184 views • 10 slides

How to Promote Deep Learning

265 views • 8 slides