Next Generation Science Standards allow for opportunities to embed technology into the digital classroom. Learn how to leverage the ISTE Standards to improve science education.
PSTA13 - iPads to Create Innovative ScientistsBen Smith
Got iPad? We will show you the best apps and how to work with students using this device. Whether you have one device or a classroom set, you will leave with ideas on how to leverage these tools for finding information, collecting and analyzing data, and communicating learning.
This model lesson will demonstrate how students can collect and share data and produce a digital report. Bring your own device to participate as a student or come observe all the action.
Manage Your Time So It Doesn't Manage YouKaren Lopez
NASA Space Apps NYC Pre-Hackathon Symposium presentation by Karen Lopez, InfoAdvisors and NASA Datanaut. Karen presents on how to successfully manage your time and deliverables in the NASA Space Apps Challenge no matter where you are participating.
SafeguardAI and Surprise Based Learning -- Protect your AI solutions from Uni...NAVER Engineering
발표자: 류봉균(EpiSys Science, Inc. 대표)
발표일: 2018.3.
In this talk, I will introduce Surprise Based Learning (SBL), a novel machine learning algorithm founded on the concepts of Complementary Discrimination Learning first introduced by Dr. Wei-Min Shen and Nobel laureate professor Herbert Simon. In contrast to most competitive learning algorithms which focus on structured learning (e.g., Bayesian Networks, Hidden Markov Models) or parameter learning (e.g., Neural Networks, Deep Learning) SBL offers the best of both worlds, meaning that it is capable of learning both the structure (i.e., number of states) and the parameters (i.e., input/output correlation) of a system.
EpiSys Science (EpiSci) is adapting SBL for several application domains. One of them is SafeguardAI, which identify when and what the DL model observes is unfamiliar, and communicate to a human supervisor, ‘I’m not sure what to do. The key insight is to embed a set of well-positioned intelligent agents inside the neural nets during the DL training process. These agents will continuously live inside a trained DL model during runtime and report out-of-distribution inputs as “surprises” or unusual behaviors. DL solutions can use these intelligent agents to safeguard its decision-making process.
I will present several experimental results that demonstrate the effectiveness of the SafeguardAI, and discuss other areas of applications.
NSTA - Using iPads to Create Innovative ScientistsBen Smith
Got iPad? We will show you the best apps and how to work with students using this device. Whether you have one device or a classroom set, you will leave with ideas on how to leverage these tools for finding information, collecting and analyzing data, and communicating their learning. Come see how to tap into your students’ creative side.
The Frontier of Deep Learning in 2020 and BeyondNUS-ISS
This talk will be a summary of the recent advances in deep learning research, current trends in the industry, and the opportunities that lie ahead.
We will discuss topics in research such as:
Transformers, GPT-3, BERT
Neural Architecture Search, Evolutionary Search
Distillation, self-learning
NeRF
Self-Attention
Also shifting industry trends such as:
The move to free data
Rising importance of 3D vision
Using synthetic data (Sim2Real)
Mobile vision & Federated Learning
PSTA13 - iPads to Create Innovative ScientistsBen Smith
Got iPad? We will show you the best apps and how to work with students using this device. Whether you have one device or a classroom set, you will leave with ideas on how to leverage these tools for finding information, collecting and analyzing data, and communicating learning.
This model lesson will demonstrate how students can collect and share data and produce a digital report. Bring your own device to participate as a student or come observe all the action.
Manage Your Time So It Doesn't Manage YouKaren Lopez
NASA Space Apps NYC Pre-Hackathon Symposium presentation by Karen Lopez, InfoAdvisors and NASA Datanaut. Karen presents on how to successfully manage your time and deliverables in the NASA Space Apps Challenge no matter where you are participating.
SafeguardAI and Surprise Based Learning -- Protect your AI solutions from Uni...NAVER Engineering
발표자: 류봉균(EpiSys Science, Inc. 대표)
발표일: 2018.3.
In this talk, I will introduce Surprise Based Learning (SBL), a novel machine learning algorithm founded on the concepts of Complementary Discrimination Learning first introduced by Dr. Wei-Min Shen and Nobel laureate professor Herbert Simon. In contrast to most competitive learning algorithms which focus on structured learning (e.g., Bayesian Networks, Hidden Markov Models) or parameter learning (e.g., Neural Networks, Deep Learning) SBL offers the best of both worlds, meaning that it is capable of learning both the structure (i.e., number of states) and the parameters (i.e., input/output correlation) of a system.
EpiSys Science (EpiSci) is adapting SBL for several application domains. One of them is SafeguardAI, which identify when and what the DL model observes is unfamiliar, and communicate to a human supervisor, ‘I’m not sure what to do. The key insight is to embed a set of well-positioned intelligent agents inside the neural nets during the DL training process. These agents will continuously live inside a trained DL model during runtime and report out-of-distribution inputs as “surprises” or unusual behaviors. DL solutions can use these intelligent agents to safeguard its decision-making process.
I will present several experimental results that demonstrate the effectiveness of the SafeguardAI, and discuss other areas of applications.
NSTA - Using iPads to Create Innovative ScientistsBen Smith
Got iPad? We will show you the best apps and how to work with students using this device. Whether you have one device or a classroom set, you will leave with ideas on how to leverage these tools for finding information, collecting and analyzing data, and communicating their learning. Come see how to tap into your students’ creative side.
The Frontier of Deep Learning in 2020 and BeyondNUS-ISS
This talk will be a summary of the recent advances in deep learning research, current trends in the industry, and the opportunities that lie ahead.
We will discuss topics in research such as:
Transformers, GPT-3, BERT
Neural Architecture Search, Evolutionary Search
Distillation, self-learning
NeRF
Self-Attention
Also shifting industry trends such as:
The move to free data
Rising importance of 3D vision
Using synthetic data (Sim2Real)
Mobile vision & Federated Learning
Video has become ubiquitous on the Internet, TV, as well as personal devices. Recognition of video content has been a fundamental challenge in computer vision for decades, where previous research predominantly focused on recognizing videos using a predefined yet limited vocabulary. Thanks to the recent development of deep learning and knowledge graph techniques, researchers in multiple communities are now striving to bridge videos with natural language in order to move beyond classification to interpretation, which should be regarded as the ultimate goal of video understanding. We will present recent advances in exploring the synergy of video understanding and language processing techniques, including video entity linking, video-language alignment, and video captioning, and discuss how domain knowledge can fit in to improve the performance.
Does deep learning solve all the machine learning problems? Where would domain knowledge fit in? While it is common in medical data analytics to incorporate domain knowledge, we focus on one emerging area in computer vision and language processing, video+language, to answer these questions.
Video has become ubiquitous on the Internet, TV, as well as personal devices. Recognition of video content has been a fundamental challenge in computer vision for decades, where previous research predominantly focused on recognizing videos using a predefined yet limited vocabulary. Thanks to the recent development of deep learning and knowledge graph techniques, researchers in multiple communities are now striving to bridge videos with natural language in order to move beyond classification to interpretation, which should be regarded as the ultimate goal of video understanding. We will present recent advances in exploring the synergy of video understanding and language processing techniques, including video entity linking, video-language alignment, and video captioning, and discuss how domain knowledge can fit in to improve the performance.
Most of the time, when you hear about Artificial Intelligence (AI), people talk about new algorithms or even the computation power needed to train them. But Data is one of the most important factors in AI.
Ofer Ron, senior data scientist at LivePerson.
Recently, I've had the pleasure of presenting an introduction to Data Science and data driven products at DevconTLV
I focused this talk around the basic ideas of data science, not the technology used, since I thought that far too many times companies and developers rush to play around with "big data" related technologies, instead of figuring out what questions they want to answer, and whether these answers form a successful product.
Download this webinar for free: http://mstnr.me/2hPUamd
Technology is one of five essential components of the digital story. Analytics provide us with vital information to track and measure audience behavior, so we can extend the reach and impact of our storytelling efforts across all of our communications channels. What do you measure, and how do you use that data to refine your story? Join us for this webinar to get your analytics game on!
What You Will Learn
• Learn about the most important metrics for digital stories, and how analytics relate to the four other essential components of a digital story.
• Discover techniques for measuring those metrics on your sites and social media accounts, including testing different versions of content.
• Gain a framework for analyzing information and making smart, data-driven decisions about content and design.
Intro to Data Science for Non-Data ScientistsSri Ambati
Erin LeDell and Chen Huang's presentations from the Intro to Data Science for Non-Data Scientists Meetup at H2O HQ on 08.20.15
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
Tom DeMarco states that “You can’t control what you can’t measure”, but how much can we change and control (with) what we measure? This talk investigates the opportunities and limits of data-driven software engineering, shows which opportunities lie ahead of us when we engage in mining and analyzing software engineering process data, but also highlights important factors that influence the success and adaptability of data-based improvement approaches.
Analytics-Enabled Experiences: The New Secret WeaponDatabricks
Tracking and analyzing how our individual products come together has always been an elusive problem for Steelcase. Our problem can be thought of in the following way: “we know how many Lego pieces we sell, yet we don’t know what Lego set our customers buy.” The Data Science team took over this initiative, which resulted in an evolution of our analytics journey. It is a story of innovation, resilience, agility and grit.
The effects of the COVID-19 pandemic on corporate America shined the spotlight on office furniture manufacturers to solve for ways on which the office can be made safe again. The team would have never imagined how relevant our work on product application analytics would become. Product application analytics became an industry priority overnight.
The proposal presented this year is the story of how data science is helping corporations bring people back to the office and set the path to lead the reinvention of the office space.
After groundbreaking milestones to overcome technical challenges, the most important question is: What do we do with this? How do we scale this? How do we turn this opportunity into a true competitive advantage? The response: stop thinking about this work as a data science project and start to think about this as an analytics-enabled experience.
During our session we will cover the technical elements that we overcame as a team to set-up a pipeline that ingests semi-structured and unstructured data at scale, performs analytics and produces digital experiences for multiple users.
This presentation will be particularly insightful for Data Scientists, Data Engineers and analytics leaders who are seeking to better understand how to augment the value of data for their organization
Discovery and Open Data: slides from #discopen session at JISC cross programme meeting in April 2012. Author: Amber Thomas, JISC. Discusses the data space around discovery issues in education and research, with a focus on open data. CC BY. Please see slide 2 for permissions.
This presentation anchors best practices for Enterprise Data Science based on Microsoft's "Team Data Science Process". The talk includes introducing the concepts, describing some real-world advice for project planning, and discusses typical titles of professionals who make enterprise data science successful. These techniques also apply for AI (artificial intelligence), deep learning, machine learning, and advanced analytics.
Come see how to tap into your students’ creative side. We will demonstrate, including student examples, how to enhance your classroom using technology.
Video has become ubiquitous on the Internet, TV, as well as personal devices. Recognition of video content has been a fundamental challenge in computer vision for decades, where previous research predominantly focused on recognizing videos using a predefined yet limited vocabulary. Thanks to the recent development of deep learning and knowledge graph techniques, researchers in multiple communities are now striving to bridge videos with natural language in order to move beyond classification to interpretation, which should be regarded as the ultimate goal of video understanding. We will present recent advances in exploring the synergy of video understanding and language processing techniques, including video entity linking, video-language alignment, and video captioning, and discuss how domain knowledge can fit in to improve the performance.
Does deep learning solve all the machine learning problems? Where would domain knowledge fit in? While it is common in medical data analytics to incorporate domain knowledge, we focus on one emerging area in computer vision and language processing, video+language, to answer these questions.
Video has become ubiquitous on the Internet, TV, as well as personal devices. Recognition of video content has been a fundamental challenge in computer vision for decades, where previous research predominantly focused on recognizing videos using a predefined yet limited vocabulary. Thanks to the recent development of deep learning and knowledge graph techniques, researchers in multiple communities are now striving to bridge videos with natural language in order to move beyond classification to interpretation, which should be regarded as the ultimate goal of video understanding. We will present recent advances in exploring the synergy of video understanding and language processing techniques, including video entity linking, video-language alignment, and video captioning, and discuss how domain knowledge can fit in to improve the performance.
Most of the time, when you hear about Artificial Intelligence (AI), people talk about new algorithms or even the computation power needed to train them. But Data is one of the most important factors in AI.
Ofer Ron, senior data scientist at LivePerson.
Recently, I've had the pleasure of presenting an introduction to Data Science and data driven products at DevconTLV
I focused this talk around the basic ideas of data science, not the technology used, since I thought that far too many times companies and developers rush to play around with "big data" related technologies, instead of figuring out what questions they want to answer, and whether these answers form a successful product.
Download this webinar for free: http://mstnr.me/2hPUamd
Technology is one of five essential components of the digital story. Analytics provide us with vital information to track and measure audience behavior, so we can extend the reach and impact of our storytelling efforts across all of our communications channels. What do you measure, and how do you use that data to refine your story? Join us for this webinar to get your analytics game on!
What You Will Learn
• Learn about the most important metrics for digital stories, and how analytics relate to the four other essential components of a digital story.
• Discover techniques for measuring those metrics on your sites and social media accounts, including testing different versions of content.
• Gain a framework for analyzing information and making smart, data-driven decisions about content and design.
Intro to Data Science for Non-Data ScientistsSri Ambati
Erin LeDell and Chen Huang's presentations from the Intro to Data Science for Non-Data Scientists Meetup at H2O HQ on 08.20.15
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
Tom DeMarco states that “You can’t control what you can’t measure”, but how much can we change and control (with) what we measure? This talk investigates the opportunities and limits of data-driven software engineering, shows which opportunities lie ahead of us when we engage in mining and analyzing software engineering process data, but also highlights important factors that influence the success and adaptability of data-based improvement approaches.
Analytics-Enabled Experiences: The New Secret WeaponDatabricks
Tracking and analyzing how our individual products come together has always been an elusive problem for Steelcase. Our problem can be thought of in the following way: “we know how many Lego pieces we sell, yet we don’t know what Lego set our customers buy.” The Data Science team took over this initiative, which resulted in an evolution of our analytics journey. It is a story of innovation, resilience, agility and grit.
The effects of the COVID-19 pandemic on corporate America shined the spotlight on office furniture manufacturers to solve for ways on which the office can be made safe again. The team would have never imagined how relevant our work on product application analytics would become. Product application analytics became an industry priority overnight.
The proposal presented this year is the story of how data science is helping corporations bring people back to the office and set the path to lead the reinvention of the office space.
After groundbreaking milestones to overcome technical challenges, the most important question is: What do we do with this? How do we scale this? How do we turn this opportunity into a true competitive advantage? The response: stop thinking about this work as a data science project and start to think about this as an analytics-enabled experience.
During our session we will cover the technical elements that we overcame as a team to set-up a pipeline that ingests semi-structured and unstructured data at scale, performs analytics and produces digital experiences for multiple users.
This presentation will be particularly insightful for Data Scientists, Data Engineers and analytics leaders who are seeking to better understand how to augment the value of data for their organization
Discovery and Open Data: slides from #discopen session at JISC cross programme meeting in April 2012. Author: Amber Thomas, JISC. Discusses the data space around discovery issues in education and research, with a focus on open data. CC BY. Please see slide 2 for permissions.
This presentation anchors best practices for Enterprise Data Science based on Microsoft's "Team Data Science Process". The talk includes introducing the concepts, describing some real-world advice for project planning, and discusses typical titles of professionals who make enterprise data science successful. These techniques also apply for AI (artificial intelligence), deep learning, machine learning, and advanced analytics.
Come see how to tap into your students’ creative side. We will demonstrate, including student examples, how to enhance your classroom using technology.
Normal Labour/ Stages of Labour/ Mechanism of LabourWasim Ak
Normal labor is also termed spontaneous labor, defined as the natural physiological process through which the fetus, placenta, and membranes are expelled from the uterus through the birth canal at term (37 to 42 weeks
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
39. Sharing Data
•
•
Google Docs
• Word Processing, Data Tables, Graphs
Wikis - Warehouse of Information
•
Task: Report your data to a Wiki or through a Google Form.
Data Collection
45. • What are the goals / objectives of the project?
• Curricular
• Skills
• Technology
• Develop a rubric
• Curriculum Focus should be first
• Need a rubric area to deal with technology aspect
• Collaboration
• Problem Solving
• Communication
Assessing Technology
Integrated Projects
46. • Email: info@edtechinnovators.com
• Website: www.edtechinnovators.com
• Ben @edtechben ben@edtechinnovators.com
• Jared @rlmaderj jared@edtechinnovators.com
Questions