This was presented at RIGA COMM 2020.
Talk about what is Machine Teaching and how it can be used in task automation scenarios.
Machine Teaching is a new paradigm and approach on how to use ML/AI to solve highly specialized tasks that would normally require human validation. Creating workflow with a human in the loop that continuously improves ML model while also carefully curating high quality data.
Recent Gartner and Capgemini studies predict only around 25% of data science projects are successful and only around 15% make it to full-scale production. Of these, many degrade in performance and produce disappointing results within months of implementation. How can focusing on the desired business outcomes and business use cases throughout a data science project help overcome the odds?
Building machine learning muscle in your team & transitioning to make them do machine learning at scale. We also discuss about Spark & other relevant technologies.
Recent Gartner and Capgemini studies predict only around 25% of data science projects are successful and only around 15% make it to full-scale production. Of these, many degrade in performance and produce disappointing results within months of implementation. How can focusing on the desired business outcomes and business use cases throughout a data science project help overcome the odds?
Building machine learning muscle in your team & transitioning to make them do machine learning at scale. We also discuss about Spark & other relevant technologies.
Travis Cox, Kathy Applebaum, and Kevin McClusky from Inductive Automation will discuss key concepts and best practices, show demos, and answer questions from the audience, to help you start integrating ML into your day-to-day processes.
Learn more about:
• Practical ways to use ML in your factory or facility
• What you'll need to get started
• Existing ML tools and platforms
• And more
Looking to make your document processing operations more effective and cost-efficient with AI/ML? Learn from the experts of Provectus and Amazon Web Services (AWS) how to choose the right solution for your company! We will look into the management and engineering perspectives of AI document processing, from industry use cases and the solution map to our unique methodology for assessing available document processing solutions to Provectus IDP. Whether you are looking for a ready-made solution or you plan to build a custom solution of your own, this webinar will help you find the best option for your business.
Agenda
- Introductions
- Industry use cases
- Intelligent Document Processing (IDP) overview
- IDP Solutions map
- AWS IDP Solution
- Provectus IDP Platform
- Q&A
Intended Audience
Technology executives and decision makers, including such roles as CIO, CCO, COO, and CDO; digital transformation managers; data and ML engineers.
Presenters
Almir Davletov, IDP Subject Matter Expert, Provectus
Yaroslav Tarasyuk, Business Development, Provectus
Sonali Sahu, Sr. Solutions Architect, AWS
Interested? Learn more about Provectus Intelligent Document Processing Solution: https://provectus.com/document-processing-solution/
A "simplified guide to SMT" is about as simple as a "simplified guide to Photoshop." Professional tools require expertise. The questions are, what levels of expertise are required, how do you acquire them and what processes contribute to a successful SMT program? These fundamentals are the same whether you're planning to use an outsourcing service or preparing to operate an in-house system. This session reviews these fundamentals with examples that reference use cases with PTTools' DoMT Desktop, a commercial application with a Moses kernel.
This presentation is a part of the MosesCore project that encourages the development and usage of open source machine translation tools, notably the Moses statistical MT toolkit. MosesCore is supported by the European Commission Grant Number 288487 under the 7th Framework Programme.
For the latest updates go to http://www.statmt.org/mosescore/
or follow us on Twitter - #MosesCore
Challenges of Operationalising Data Science in Productioniguazio
The presentation topic for this meet-up was covered in two sections without any breaks in-between
Section 1: Business Aspects (20 mins)
Speaker: Rasmi Mohapatra, Product Owner, Experian
https://www.linkedin.com/in/rasmi-m-428b3a46/
Once your data science application is in the production, there are many typical data science operational challenges experienced today - across business domains - we will cover a few challenges with example scenarios
Section 2: Tech Aspects (40 mins, slides & demo, Q&A )
Speaker: Santanu Dey, Solution Architect, Iguazio
https://www.linkedin.com/in/santanu/
In this part of the talk, we will cover how these operational challenges can be overcome e.g. automating data collection & preparation, making ML models portable & deploying in production, monitoring and scaling, etc.
with relevant demos.
(Recent) technology trends and bridges to gap in the localization industryLoctimize GmbH
Slides of the keynote presentation held by Daniel Zielinski during the frist Egyptian conference on Translation, Localization and Interpreting in Cairo on April 16, 2019
AI algorithms offer great promise in criminal justice, credit scoring, hiring and other domains. However, algorithmic fairness is a legitimate concern. Possible bias and adversarial contamination can come from training data, inappropriate data handling/model selection or incorrect algorithm design. This talk discusses how to build an open, transparent, secure and fair pipeline that fully integrates into the AI lifecycle — leveraging open-source projects such as AI Fairness 360 (AIF360), Adversarial Robustness Toolbox (ART), the Fabric for Deep Learning (FfDL) and the Model Asset eXchange (MAX).
Travis Cox, Kathy Applebaum, and Kevin McClusky from Inductive Automation will discuss key concepts and best practices, show demos, and answer questions from the audience, to help you start integrating ML into your day-to-day processes.
Learn more about:
• Practical ways to use ML in your factory or facility
• What you'll need to get started
• Existing ML tools and platforms
• And more
One of the most popular buzz words nowadays in the technology world is “Machine Learning (ML).” Most economists and business experts foresee Machine Learning changing every aspect of our lives in the next 10 years through automating and optimizing processes. This is leading many organizations to seek experts who can implement Machine Learning into their businesses.
The paper will be written for statistical programmers who want to explore Machine Learning career, add Machine Learning skills to their experiences or enter a Machine Learning fields. The paper will discuss about personal journey to become to a Machine Learning Engineer from a statistical programmer. The paper will share my personal experience on what motivated me to start Machine Learning career, how I started it, and what I have learned and done to be a Machine Learning Engineer. In addition, the paper will also discuss the future of Machine Learning in Pharmaceutical Industry, especially in Biometric department.
GenerativeAI and Automation - IEEE ACSOS 2023.pptxAllen Chan
Generative AI has been rapidly evolving, enabling different and more sophisticated interactions with Large Language Models (LLMs) like those available in IBM watsonx.ai or Meta Llama2. In this session, we will take a use case based approach to look at how we can leverage LLMs together with existing automation technologies like Workflow, Content Management, and Decisions to enable new solutions.
An AI Maturity Roadmap for Becoming a Data-Driven OrganizationDavid Solomon
The initial version of a maturity roadmap to help guide businesses when adopting AI technology into their workflow. IBM Watson Studio is referenced as an example of technology that can help in accelerating the adoption process.
Delivering Machine Learning Solutions by fmr Sears Dir of PMProduct School
Main takeaways:
- Key stages in the Data Science process
- Unique challenges ML products present
- Opportunities for Product Managers to make a big impact
UTICamp-2020. Is translation automation a myth or a reality?UTICamp
Speaker: Istvan Lengyel
Smaller translation providers face very different realities from the largest companies in the sector. In reality, the differentiator is not as much technology as developing processes together with their customers.
With the proliferation of small and frequent jobs, the industry is already seeing a move away from the “translations with love”, yet many company owners argue that the automation of processes in the translation industry is not possible, or at least not profitable. In this presentation I will talk about the many variations and aspects in translation projects that make automation difficult, and I will also look at the skills and qualities of project managers that will be those colleagues that bring your company to the next level. I will also discuss some of the lesser-known middleware tools that are worth knowing if you are interested in moving towards automation. I make an attempt to give participants both a profile that they should be looking for when hiring a “different” project manager and some recommendations on how to start instilling the culture of automation into their daily work.
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
More Related Content
Similar to Machine Teaching for workflow automation RIGA COMM 2020
Travis Cox, Kathy Applebaum, and Kevin McClusky from Inductive Automation will discuss key concepts and best practices, show demos, and answer questions from the audience, to help you start integrating ML into your day-to-day processes.
Learn more about:
• Practical ways to use ML in your factory or facility
• What you'll need to get started
• Existing ML tools and platforms
• And more
Looking to make your document processing operations more effective and cost-efficient with AI/ML? Learn from the experts of Provectus and Amazon Web Services (AWS) how to choose the right solution for your company! We will look into the management and engineering perspectives of AI document processing, from industry use cases and the solution map to our unique methodology for assessing available document processing solutions to Provectus IDP. Whether you are looking for a ready-made solution or you plan to build a custom solution of your own, this webinar will help you find the best option for your business.
Agenda
- Introductions
- Industry use cases
- Intelligent Document Processing (IDP) overview
- IDP Solutions map
- AWS IDP Solution
- Provectus IDP Platform
- Q&A
Intended Audience
Technology executives and decision makers, including such roles as CIO, CCO, COO, and CDO; digital transformation managers; data and ML engineers.
Presenters
Almir Davletov, IDP Subject Matter Expert, Provectus
Yaroslav Tarasyuk, Business Development, Provectus
Sonali Sahu, Sr. Solutions Architect, AWS
Interested? Learn more about Provectus Intelligent Document Processing Solution: https://provectus.com/document-processing-solution/
A "simplified guide to SMT" is about as simple as a "simplified guide to Photoshop." Professional tools require expertise. The questions are, what levels of expertise are required, how do you acquire them and what processes contribute to a successful SMT program? These fundamentals are the same whether you're planning to use an outsourcing service or preparing to operate an in-house system. This session reviews these fundamentals with examples that reference use cases with PTTools' DoMT Desktop, a commercial application with a Moses kernel.
This presentation is a part of the MosesCore project that encourages the development and usage of open source machine translation tools, notably the Moses statistical MT toolkit. MosesCore is supported by the European Commission Grant Number 288487 under the 7th Framework Programme.
For the latest updates go to http://www.statmt.org/mosescore/
or follow us on Twitter - #MosesCore
Challenges of Operationalising Data Science in Productioniguazio
The presentation topic for this meet-up was covered in two sections without any breaks in-between
Section 1: Business Aspects (20 mins)
Speaker: Rasmi Mohapatra, Product Owner, Experian
https://www.linkedin.com/in/rasmi-m-428b3a46/
Once your data science application is in the production, there are many typical data science operational challenges experienced today - across business domains - we will cover a few challenges with example scenarios
Section 2: Tech Aspects (40 mins, slides & demo, Q&A )
Speaker: Santanu Dey, Solution Architect, Iguazio
https://www.linkedin.com/in/santanu/
In this part of the talk, we will cover how these operational challenges can be overcome e.g. automating data collection & preparation, making ML models portable & deploying in production, monitoring and scaling, etc.
with relevant demos.
(Recent) technology trends and bridges to gap in the localization industryLoctimize GmbH
Slides of the keynote presentation held by Daniel Zielinski during the frist Egyptian conference on Translation, Localization and Interpreting in Cairo on April 16, 2019
AI algorithms offer great promise in criminal justice, credit scoring, hiring and other domains. However, algorithmic fairness is a legitimate concern. Possible bias and adversarial contamination can come from training data, inappropriate data handling/model selection or incorrect algorithm design. This talk discusses how to build an open, transparent, secure and fair pipeline that fully integrates into the AI lifecycle — leveraging open-source projects such as AI Fairness 360 (AIF360), Adversarial Robustness Toolbox (ART), the Fabric for Deep Learning (FfDL) and the Model Asset eXchange (MAX).
Travis Cox, Kathy Applebaum, and Kevin McClusky from Inductive Automation will discuss key concepts and best practices, show demos, and answer questions from the audience, to help you start integrating ML into your day-to-day processes.
Learn more about:
• Practical ways to use ML in your factory or facility
• What you'll need to get started
• Existing ML tools and platforms
• And more
One of the most popular buzz words nowadays in the technology world is “Machine Learning (ML).” Most economists and business experts foresee Machine Learning changing every aspect of our lives in the next 10 years through automating and optimizing processes. This is leading many organizations to seek experts who can implement Machine Learning into their businesses.
The paper will be written for statistical programmers who want to explore Machine Learning career, add Machine Learning skills to their experiences or enter a Machine Learning fields. The paper will discuss about personal journey to become to a Machine Learning Engineer from a statistical programmer. The paper will share my personal experience on what motivated me to start Machine Learning career, how I started it, and what I have learned and done to be a Machine Learning Engineer. In addition, the paper will also discuss the future of Machine Learning in Pharmaceutical Industry, especially in Biometric department.
GenerativeAI and Automation - IEEE ACSOS 2023.pptxAllen Chan
Generative AI has been rapidly evolving, enabling different and more sophisticated interactions with Large Language Models (LLMs) like those available in IBM watsonx.ai or Meta Llama2. In this session, we will take a use case based approach to look at how we can leverage LLMs together with existing automation technologies like Workflow, Content Management, and Decisions to enable new solutions.
An AI Maturity Roadmap for Becoming a Data-Driven OrganizationDavid Solomon
The initial version of a maturity roadmap to help guide businesses when adopting AI technology into their workflow. IBM Watson Studio is referenced as an example of technology that can help in accelerating the adoption process.
Delivering Machine Learning Solutions by fmr Sears Dir of PMProduct School
Main takeaways:
- Key stages in the Data Science process
- Unique challenges ML products present
- Opportunities for Product Managers to make a big impact
UTICamp-2020. Is translation automation a myth or a reality?UTICamp
Speaker: Istvan Lengyel
Smaller translation providers face very different realities from the largest companies in the sector. In reality, the differentiator is not as much technology as developing processes together with their customers.
With the proliferation of small and frequent jobs, the industry is already seeing a move away from the “translations with love”, yet many company owners argue that the automation of processes in the translation industry is not possible, or at least not profitable. In this presentation I will talk about the many variations and aspects in translation projects that make automation difficult, and I will also look at the skills and qualities of project managers that will be those colleagues that bring your company to the next level. I will also discuss some of the lesser-known middleware tools that are worth knowing if you are interested in moving towards automation. I make an attempt to give participants both a profile that they should be looking for when hiring a “different” project manager and some recommendations on how to start instilling the culture of automation into their daily work.
Similar to Machine Teaching for workflow automation RIGA COMM 2020 (20)
How to Position Your Globus Data Portal for Success Ten Good PracticesGlobus
Science gateways allow science and engineering communities to access shared data, software, computing services, and instruments. Science gateways have gained a lot of traction in the last twenty years, as evidenced by projects such as the Science Gateways Community Institute (SGCI) and the Center of Excellence on Science Gateways (SGX3) in the US, The Australian Research Data Commons (ARDC) and its platforms in Australia, and the projects around Virtual Research Environments in Europe. A few mature frameworks have evolved with their different strengths and foci and have been taken up by a larger community such as the Globus Data Portal, Hubzero, Tapis, and Galaxy. However, even when gateways are built on successful frameworks, they continue to face the challenges of ongoing maintenance costs and how to meet the ever-expanding needs of the community they serve with enhanced features. It is not uncommon that gateways with compelling use cases are nonetheless unable to get past the prototype phase and become a full production service, or if they do, they don't survive more than a couple of years. While there is no guaranteed pathway to success, it seems likely that for any gateway there is a need for a strong community and/or solid funding streams to create and sustain its success. With over twenty years of examples to draw from, this presentation goes into detail for ten factors common to successful and enduring gateways that effectively serve as best practices for any new or developing gateway.
Navigating the Metaverse: A Journey into Virtual Evolution"Donna Lenk
Join us for an exploration of the Metaverse's evolution, where innovation meets imagination. Discover new dimensions of virtual events, engage with thought-provoking discussions, and witness the transformative power of digital realms."
Utilocate offers a comprehensive solution for locate ticket management by automating and streamlining the entire process. By integrating with Geospatial Information Systems (GIS), it provides accurate mapping and visualization of utility locations, enhancing decision-making and reducing the risk of errors. The system's advanced data analytics tools help identify trends, predict potential issues, and optimize resource allocation, making the locate ticket management process smarter and more efficient. Additionally, automated ticket management ensures consistency and reduces human error, while real-time notifications keep all relevant personnel informed and ready to respond promptly.
The system's ability to streamline workflows and automate ticket routing significantly reduces the time taken to process each ticket, making the process faster and more efficient. Mobile access allows field technicians to update ticket information on the go, ensuring that the latest information is always available and accelerating the locate process. Overall, Utilocate not only enhances the efficiency and accuracy of locate ticket management but also improves safety by minimizing the risk of utility damage through precise and timely locates.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
AI Pilot Review: The World’s First Virtual Assistant Marketing SuiteGoogle
AI Pilot Review: The World’s First Virtual Assistant Marketing Suite
👉👉 Click Here To Get More Info 👇👇
https://sumonreview.com/ai-pilot-review/
AI Pilot Review: Key Features
✅Deploy AI expert bots in Any Niche With Just A Click
✅With one keyword, generate complete funnels, websites, landing pages, and more.
✅More than 85 AI features are included in the AI pilot.
✅No setup or configuration; use your voice (like Siri) to do whatever you want.
✅You Can Use AI Pilot To Create your version of AI Pilot And Charge People For It…
✅ZERO Manual Work With AI Pilot. Never write, Design, Or Code Again.
✅ZERO Limits On Features Or Usages
✅Use Our AI-powered Traffic To Get Hundreds Of Customers
✅No Complicated Setup: Get Up And Running In 2 Minutes
✅99.99% Up-Time Guaranteed
✅30 Days Money-Back Guarantee
✅ZERO Upfront Cost
See My Other Reviews Article:
(1) TubeTrivia AI Review: https://sumonreview.com/tubetrivia-ai-review
(2) SocioWave Review: https://sumonreview.com/sociowave-review
(3) AI Partner & Profit Review: https://sumonreview.com/ai-partner-profit-review
(4) AI Ebook Suite Review: https://sumonreview.com/ai-ebook-suite-review
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
First Steps with Globus Compute Multi-User EndpointsGlobus
In this presentation we will share our experiences around getting started with the Globus Compute multi-user endpoint. Working with the Pharmacology group at the University of Auckland, we have previously written an application using Globus Compute that can offload computationally expensive steps in the researcher's workflows, which they wish to manage from their familiar Windows environments, onto the NeSI (New Zealand eScience Infrastructure) cluster. Some of the challenges we have encountered were that each researcher had to set up and manage their own single-user globus compute endpoint and that the workloads had varying resource requirements (CPUs, memory and wall time) between different runs. We hope that the multi-user endpoint will help to address these challenges and share an update on our progress here.
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I ...Juraj Vysvader
In 2015, I used to write extensions for Joomla, WordPress, phpBB3, etc and I didn't get rich from it but it did have 63K downloads (powered possible tens of thousands of websites).
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
Exploring Innovations in Data Repository Solutions - Insights from the U.S. G...Globus
The U.S. Geological Survey (USGS) has made substantial investments in meeting evolving scientific, technical, and policy driven demands on storing, managing, and delivering data. As these demands continue to grow in complexity and scale, the USGS must continue to explore innovative solutions to improve its management, curation, sharing, delivering, and preservation approaches for large-scale research data. Supporting these needs, the USGS has partnered with the University of Chicago-Globus to research and develop advanced repository components and workflows leveraging its current investment in Globus. The primary outcome of this partnership includes the development of a prototype enterprise repository, driven by USGS Data Release requirements, through exploration and implementation of the entire suite of the Globus platform offerings, including Globus Flow, Globus Auth, Globus Transfer, and Globus Search. This presentation will provide insights into this research partnership, introduce the unique requirements and challenges being addressed and provide relevant project progress.
How Recreation Management Software Can Streamline Your Operations.pptxwottaspaceseo
Recreation management software streamlines operations by automating key tasks such as scheduling, registration, and payment processing, reducing manual workload and errors. It provides centralized management of facilities, classes, and events, ensuring efficient resource allocation and facility usage. The software offers user-friendly online portals for easy access to bookings and program information, enhancing customer experience. Real-time reporting and data analytics deliver insights into attendance and preferences, aiding in strategic decision-making. Additionally, effective communication tools keep participants and staff informed with timely updates. Overall, recreation management software enhances efficiency, improves service delivery, and boosts customer satisfaction.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
In the ever-evolving landscape of technology, enterprise software development is undergoing a significant transformation. Traditional coding methods are being challenged by innovative no-code solutions, which promise to streamline and democratize the software development process.
This shift is particularly impactful for enterprises, which require robust, scalable, and efficient software to manage their operations. In this article, we will explore the various facets of enterprise software development with no-code solutions, examining their benefits, challenges, and the future potential they hold.
4. Emergn’s Machine
Learning Lab
Our team's core competencies:
• Business understanding of how to profit
from ML
• Machine learning development
• Deep learning and reinforcement learning
• Data visualization
• Algorithms and ML techniques
• Data processing, cleaning and preparation
OUR TECHNOLOGY STACK
We have established and run the largest ML community
in the Baltics with 1260 field experts as members.
All these activities currently makes our company the
No. 1 Choice for young and experience ML talents.
Machine learning models
Tools and programming languages:
• Python
• TensorFlow, TensorBoard
• R ,OpenCV, Caffe2
• KNIME
• Azure Machine Learning
Studio
• C, C++
Deployment techniques
Platforms and environments:
• Stand alone models
• SAP Hana2
• Microsoft Azure (Cortana
intelligences suite)
• SQL Server
We are partnering with GDEXA to help enable the young
generation with highly demanded skills like applied
AI/ML, Big Data Analytics and Cloud Applications.
6. Business automation
challenge
From automation with replacement of
humans to augmentation and
empowerment of subject matter experts.
We predict that companies who use
augmented automation technologies to
empower their environments and educate
their people on how to use them for better,
more predictable outcomes, will win by
providing the best service and building
better products.
• Wheels for the mind
• Find a comfortable level of automation
7. Why are we looking for
machine learning
(ML) alternatives?
ML for automation and
workflows should:
• Be transparent and interactive for
business users
• Include natural language-based
solutions where humans have better
comprehension
• Understand context and learning
from smaller data sets
• ML models should be verified and
monitored
AI director at
Facebook
YANN LECUN
ATARI GAME
Self-driving cars need
millions of hours of
training to reach
human level trained in
about 20 hours.
In 80 hours machine
will reach human level
aquired by 15 minutes.
8. Change of paradigm
Key differences
• Role of subject matter expert (SME) changes – using our tool, SME trains/provides the logic to improve the model.
• SME is integral to the success, needs to be empowered and have the tools to do their work better.
• The "one and done" approach is not flexible/doesn't allow for market changes nor incremental knowledge.
MACHINE TEACHING
MACHINE LEARNING
9. Iterative machine teaching process
For use cases such as:
• Email/text/document
classification
• Email/text/document
anonymization
• Entity extraction
SME
DATA SCIENTIST
Initial
model
training
Models could be
regularly monitored
by SME
AUTOMATION
WORKFLOW
CLASSIFICATION
MODEL
10. Tools for model quality inspection
Machine Teaching
administration tools
help business users
and ML Power Users
control classification
model quality.
12. Finding quick wins
ROUTINE OPERATIONS
• RPA Robots
• Machine Learning
• OCR + Data Extraction
REPETITIVE
COGNITIVE TASKS
COLLABORATION
WORKFLOWS
• Machine Learning
• Rule Engines • Interactive applications
• Workflows
• Data Enrichment
DECISION MAKING
AND SUPPORT
• AI
• Process Mining
• Document classification
• Automation translation
• Collaboration apps
• Approvals
• Case management
• Prioritization of work
• Analysis
• Data Extraction
• Copy data
• Enter data
• Sort documents
FREE UP PEOPLE TIME SUPPORT SHIFT TO DIGITAL OPERATING MODEL
TASK AUTOMATION WORKFLOW AUTOMATION DECISION AUTOMATION
• Machine Learning
Natural
Language
based
use-cases
13. Automation of the document flow
DOCUMENT LIFE-CYCLE
RECEIVE
DOCUMENT
PROCESS
DOCUMENT
ARCHIVING
• Highly manual
• Need decision making, involving knowledge worker to do manual tasks
• Text comprehension (SME)
• Fraught with errors
• Difficult to research/go back, to find things
• Time consuming
• Not possible when scale is large
14. Automation of the document flow
DOCUMENT LIFE-CYCLE
RECEIVE
DOCUMENT
SAVE
DOCUMENT
EXTRA
META DATA
Document and
form recognition
using OCR
• Be physical
document or
email or video
any format can
be input
DOCUMENT
ROUTING
DOCUMENT
PUBLISHING
ARCHIVING
Meta-data
extraction
• Key fields
• Key words
• In text
• e.g. PO #
• Subject
• Amount
Document
classification
and routing e.g.
• Classification
• Invoice routing
• Approval,
level, direct
forward to
finance
Document
anonymization
and masking e.g.
• Bank and
personal info
Document
archiving by
classification e.g.
• Archiving based
on classification: in
cloud or on-site
HOT WARM COLD
15. Information extraction from documents
CLIENT RECORD
CLIENT RELATED
DOCUMENTS AND KEYWORDS DATA
EXTRACTION
MODEL
*Client information is
automatically enriched.
Company: BNP Paribas*
Title:
Name: Tom Barnes*
Other information:
Meta data
Retrieving information from text and documents helps you to obtain data
that can and must supplement the information of certain accounting cards.
DATA
EXTRACTION
CONFIG
16. Document classification
Email
• By title
• By object
• By action
Mail
• A
• B
• C
Contract
Application
Invoice
CLASS CATALOG
The document class is
determined by the
organizational
documents/text
classification catalog
Training of document class catalogues and document
classification algorithm by business user – specialist
The classification of documents results in the identification of the document class and can use it to
further process the document, usually routing and storing it in an appropriate document process.
DOCUMENT
CLASSIFICATION
MODEL
DOCUMENT
CLASS
17. Document anonymization
The purpose of anonymizing documents/text is to cover all or part
of sensitive information prior to publication of the document/text.
Person 1, social security number,
living, Address 1, closed contract
Contact Number, with Company
ABC for Contract Title
DATA
MASKING
George Bennett,
Social security number
989384843*****, address,
***** street *
DOCUMENT
ANONYMIZATION
ANONYMIZATED
DOCUMENT
ANONYMIZATED
TEXT
ANONYMIZATION
CONFIGURATION
ANONYMIZATED
DOCUMENT
18. Machine
Teaching (MT)
Tool
Machine
Learning (ML)
Solution
Technical architecture
SET UP AS AN INTERNAL TOOL
ON-PREMISE SERVICE
MODULAR STRUCTURE
SME/IT:
• MT Tool with UI for training & analytics
• Custom integrations possible
• Endpoints for production scenario provided
Data Scientist:
• ML model exchangeable - has standardized endpoints
• Data and integration – as needed
PYTHON
CAN BE INTEGRATED INTO EXISTING WORKFLOW MODEL
MT DATABASE
MODEL DATA
ML SOLUTION
MT SERVICE
CUSTOM
INTEGRATION &
PRODUCTION
MT TOOL
21. How to get most value from machine
teaching for Natural Language
Processing (NLP) and Non-NLP models
IN NLP MODELS
• Objective – Create
Optimal data set for best
known optimal models
• Use for data labeling
and data preparation
IN NON-NLP MODELS
• Objective – Find
optimal/best model with
existing data
• Use for model monitoring
and verification
Machine Learning is the subfield of
computer science that, according to Arthur
Samuel in 1959, gives “computers the ability
to learn without being explicitly programmed.”
NLP
Artificial
Intelligence
Machine
Learning
Statistics
22. Let's stay connected
Contact us at info@emergn.com
for an individual demo.
Follow us: @emergn
MUNTIS RUDZITIS
Lead Data Scientist
at Emergn
https://www.linkedin.com/in/muntis-rudzitis/
ARIADNA KRAMKOVSKA
Machine Learning Developer
at Emergn
https://www.linkedin.com/in/ariadnakramkovska/