15:03

Part 5 | Big Data, Onion Architecture, Open Source, Multi-cloud ...

09:32

Part 6 | Architecture, AI for Document Classification, API playground ...

10:49

Part 4 | ECM, Challenges, Solutions and Cloud

07:17

Part 3 | Enterprise Content Management

03:02

Part 2 | ECM, Optimal Systems, Artificial Intelligence

02:09

Part 1 | Introduction

02:13

Deep Space and Deep Data | part 1 - intersection and legal aspects

04:09

Deep Space and Deep Data | part 8 - Serbian Case for Space Foundation

02:48

Deep Space and Deep Data | part 7 - Private Satellite Data Providers

03:36

Deep Space and Deep Data | part 6 - Copernicus and open access satellite data

02:40

Deep Space and Deep Data | part 5 - Position of Serbia in the Space Domain

11:17

Deep Space and Deep Data | part 4 - Important Legal Principles

03:38

Deep Space and Deep Data | part 3 - Space Treaties

03:11

Deep Space and Deep Data | part 2 - What is Space Law

06:30

LipNet, Surveillance, Biometry, Computational photography ..

04:20

Computer Vision Applications | Deepfakes

05:45

Computer Vision Applications | Self-Driving

07:34

Computer Vision Applications | Mixed Reality and HoloPortation

01:33

Machine "vs" Human (2020)

01:26

Arrival of Deep Learning (2012)

01:46

Early Days of Computer Vision (80s)

01:31

Early Days of Computer Vision (60s)

00:56

Pie & AI: Belgrade | Computer Vision

03:01

Computer Vision - Introduction

02:25

Conflicts created by AI

01:14

Does AI Steal Jobs?

02:50

Should We Be Afraid of AI?

02:03

Innovators

07:11

The Conflict Cycle of Innovation

04:18

Solution to Conflict

04:48

Cloud Vs. Edge Computing

04:27

Artificial Intelligence BattleGround | Cloud vs Edge

04:44

Hardware and Software

02:45

FPGAs made Easy: Sparse Convolutional AI

06:31

AI is just Mathematics

02:12

From Perceptrons to Artificial Intelligence

02:29

Innovation: AI and Neural Networks

00:58

AI and Conflict | Hardware to Software, Edge to Datacenter

01:02

Welcome Note

00:19

Thank You Note

02:05

ICU Simulation Study

01:43

Model Reliability

07:08

Results

00:48

Why do we expect TPC to do well on LoS

03:31

Loss Function

04:23

Model

04:29

Temporal Convolution

02:49

What do we want the model to extract?

03:02

Data: Electronic Health Records in Intensive Care

02:28

Length of Stay Labels

01:11

Remaining Length of Stay Prediction

02:36

Predicting Length of Stay in Intensive Care

02:10

Deep Learning

02:34

What is "Deep Learning"?

04:31

What do they contain?

01:02

What are Electronic Health Records?

02:54

Welcome Note

02:04

Deep Learning Approaches to Electronic Health Records

01:04

Overview