Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts

•Download as PPTX, PDF•

0 likes•192 views

OMM Solutions GmbH

OMM TECHtalks #1 www.tech-talks.eu

Software

OMM Solutions
TECHtalk #1
www.omm-solutions.de
30.03.2017 < OMM Solutions GmbH > 1
www.tech-talks.eu

Einmal im Monat ist TECHtalk Zeit! First come first served!
< OMM Solutions GmbH > 2

Talk: Building an intelligent Pullup-Classifier
Speaker: Olaf Horstmann
3< OMM Solutions GmbH >

• should COUNT the pullups
• should detect WHO
• should classify the QUALITY
The Goal
30.03.2017 < OMM Solutions GmbH > 5

Image from: http://www.instructables.com/id/Pull-Up-Counter/
Existing solutions
30.03.2017 < OMM Solutions GmbH > 6

✓ COUNT
× WHO
× QUALITY
Can we use it?
30.03.2017 < OMM Solutions GmbH > 8

The Pressure-Sensor
Iteration #1
30.03.2017 < OMM Solutions GmbH > 9

Let‘s try it!
30.03.2017 < OMM Solutions GmbH > 10

OKAY…
30.03.2017 < OMM Solutions GmbH > 11

The Ultrasonic-Sensor
Iteration #2
30.03.2017 < OMM Solutions GmbH > 12

• Only works on perpendicular angles (+/-15°)
• Only works on „flat“ surfaces (hair or clothes = bad)
• You can hear it when it is quiet
BUT…
30.03.2017 < OMM Solutions GmbH > 15

An optical sensor
Iteration #3
30.03.2017 < OMM Solutions GmbH > 16

Success
30.03.2017 < OMM Solutions GmbH > 19

• Cost more than the other sensors
• Inaccurate/slow > 2m
• Might not work very well in direct sunlight (did not test)
Any Drawbacks?
30.03.2017 < OMM Solutions GmbH > 20

• Collected data from different people
• Prepate the data
• Implement an AI to classify the data
Now what?
30.03.2017 < OMM Solutions GmbH > 21

Collecting/Comparing Data
30.03.2017 < OMM Solutions GmbH > 22

• Algorithm to detect individual pullups (=> count)
• Label each data-set manually (=> who & quality)
Data-Preparation
30.03.2017 < OMM Solutions GmbH > 23

Data-Preparation
30.03.2017 < OMM Solutions GmbH > 24

• Throw in the raw data (~200 pullups)
• Train it
• See what happens
• => accuracy ~60%
With Tensorflow
AI Iteration #1
30.03.2017 < OMM Solutions GmbH > 25

• More data (a lot more!)
• Adjust the network (not really better)
• Use meta-data instead of raw data
How can we improve this?
30.03.2017 < OMM Solutions GmbH > 26

• Using ~15 different meta-data-points
• => accuracy ~85%
AI Iteration #2
30.03.2017 < OMM Solutions GmbH > 27

• Normalize data (high values are bad!)
• …and more data!
…but there‘s still room for improvements
It‘s Okay…
30.03.2017 < OMM Solutions GmbH > 28

• Normalized data
• => accuracy at +90%
AI Iteration #3
30.03.2017 < OMM Solutions GmbH > 29

„The Product“
30.03.2017 < OMM Solutions GmbH > 30

• Data preparation is probably the most important step
• Visualizing the data helps analyzing it
• Less data can be compensated by transforming the data first
• Having more classes can help with the accuracy of the whole model
• More data is always better
Learnings
30.03.2017 < OMM Solutions GmbH > 31

Vielen Dank für Eure Aufmerksamkeit!
32< OMM Solutions GmbH >

Ihr persönlicher Ansprechpartner
Fragen oder Interesse?
< OMM Solutions GmbH > 33
Olaf Horstmann
Technology & Innovation
OMM Solutions GmbH
Vor dem Lauch 4
70567 Stuttgart
Germany
oh@omm-solutions.de
+49 (0)711 75 86 46 04

34< OMM Solutions GmbH >
www.omm-solutions.de
OMM Solutions GmbH
Vor dem Lauch 4
70567 Stuttgart
Geschäftsführer
Martin Allmendinger
Malte Horstmann
Olaf Horstmann
Kontakt
Telefon: +49 711 6747 051-0
E-Mail: info@omm-solutions.de
Umsatzsteuer-ID: DE295716572
Sitz der Gesellschaft: Stuttgart
Amtsgericht Stuttgart, HRB 749562
Impressum

Similar to Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts

Tips for Introducing Automation in QA Process

KarthikeyanRajendran27

CP Optimizer is a generic Constraint Programming (CP) based system to model and solve scheduling problems (among other combinatorial problems). It provides an algebraic language with simple mathematical concepts such as intervals or functions to capture the temporal dimension of scheduling problems in a combinatorial optimization framework. From the very beginning, CP Optimizer was designed with the goal to provide a similar experience as Mathematical Programming (MP) tools like CPLEX, with a strong focus on usability. In particular CP Optimizer implements a model & run paradigm that does not require the user to understand Constraint Programming or scheduling algorithms: declarative modeling is the only thing that matters. The automatic search provides good out of the box performance and is continuously improving from version to version. The convergence with MP goes even further, with a convergence of the tools and functionalities around the engine like an input/output format, modeling assistance with warnings and conflict refiner, interactive executable, etc. These tools accelerate the development and maintenance of models for complex industrial scheduling problems that will be efficiently solved by the automatic search. This tutorial, heavily illustrated with examples, gives an overview of CP Optimizer for scheduling. No prior knowledge of Constraint Programming is required.

A (Not So Short) Introduction to CP Optimizer for Scheduling

Philippe Laborie

Webinar: Performance Tuning + Optimization

MongoDB

Can We Automate Predictive Analytics

odsc

XGBoost @ Fyber

Daniel Hen

Pomppt

arggarg

Artificial Intelligence and Machine Learning are becoming increasingly accessible. Starting from example use cases, I’ll aim at demystifying how they work and how they improve businesses in 3 areas: increasing the number of customers, serving them better, and serving them more efficiently. I’ll show how machines can use data to automatically learn business rules and make predictions, that can then be used to make better decisions. I’ll introduce the main concepts of ML, its possibilities, its limitations, and I’ll give tips on framing the right problems for your company to tackle. Louis Dorard is the author of Bootstrapping Machine Learning, a co-founder of PAPIs, and an independent consultant. His goal is to help people use new machine learning technologies to make their apps and businesses smarter. He does this by writing, speaking and teaching.

A business level introduction to Artificial Intelligence - Louis Dorard @ PAP...

PAPIs.io

Agile Software Development – Why all the fuzz?

OMM Solutions GmbH

O.M.S. High Tech CNC parts

O.M.S. s.r.l.

Join CCG and Microsoft for a hands-on demonstration of Azure’s machine learning capabilities. During the workshop, we will: - Hold a Machine Learning 101 session to explain what machine learning is and how it fits in the analytics landscape - Demonstrate Azure Databricks’ capabilities for building custom machine learning models - Take a tour of the Azure Machine Learning’s capabilities for MLOps, Automated Machine Learning, and code-free Machine Learning By the end of the workshop, you’ll have the tools you need to begin your own journey to AI.

Machine Learning with Azure and Databricks Virtual Workshop

DA lecture 3.pptx

Simulation (qa ii)

BigData @ comScore

In manufacturing today, many types of image analysis are being performed to meet the different needs of various industries and applications. For this reason, many imaging software and microscope companies have created software that serves as a “jack of all trades,” giving you a variety of tools that seemingly allow you to accomplish just about anything. The problem with these broad software tools is that there is more than one way to perform many imaging processes, and there can be lots of variability between different operators. Solution-based software, on the other hand, takes a look at very specific customer applications and processes and maps them step-by-step into the software. This creates a much easier to use piece of software with less variation between operators, and allows for more repeatable results in your analysis. For more information, visit: http://www.olympus-ims.com/en/insight/customizable-imaging-software-better-than-jack-of-all-trades/

Why Customizable Imaging Software is Better than a "Jack of All Trades"

Olympus IMS

Mtc strategy-briefing-houston-pd m-05212018-3

Dania Kodeih

Similar to Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts (15)

Tips for Introducing Automation in QA Process

A (Not So Short) Introduction to CP Optimizer for Scheduling

Webinar: Performance Tuning + Optimization

Can We Automate Predictive Analytics

XGBoost @ Fyber

Pomppt

A business level introduction to Artificial Intelligence - Louis Dorard @ PAP...

Agile Software Development – Why all the fuzz?

O.M.S. High Tech CNC parts

Machine Learning with Azure and Databricks Virtual Workshop

DA lecture 3.pptx

Simulation (qa ii)

BigData @ comScore

Why Customizable Imaging Software is Better than a "Jack of All Trades"

Mtc strategy-briefing-houston-pd m-05212018-3

Recently uploaded

(Vivek)Call Us, 8448380779,Call girls in Delhi NCr – We Offer best in class call girls. escort Service At Affordable Price At low Rate with Space Night 8000 We Are One Of The Oldest Escort and Call girls Agencies in Delhi. You Will Find That Our Female Escorts Are Full Of Fun, Sexy And They Would Love Enjoy Your Company. We Have A Fantastic Selection Of Escort Ladies Available For In-Calls As Well As Out-Calls. Our Escorts Are Not Only Beautiful But All Have Great Personalities Making Them The Perfect Companion For Any Occasion. In-Call:- You Can Come At Our Place in Delhi Our place Which Is Very Clean Hygienic 100% safe Accommodation. Out-Call:- You have To Come Pick The Girl From My Place We Are Also Provide Door Step Services (Delhi Ncr, Noida, Gurgaon, Faridabad, Ghaziabad Note:- Pic Collectors Time Passers Bargainers Stay Away As We Respect The Value For Your Money Time And Expect The Same From You Hygienic:- Full Ac room And Clean Rooms Available In Hotel 24 * 7 Hourly In Delhi NCR More Details, With WhatsApp Number, +91-8448380779

call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️

Delhi Call girls

In the realm of real-time applications, Large Language Models (LLMs) have long dominated language-centric tasks, while tools like OpenCV have excelled in the visual domain. However, the future (maybe) lies in the fusion of LLMs and deep learning, giving birth to the revolutionary concept of Large Action Models (LAMs). Imagine a world where AI not only comprehends language but mimics human actions on technology interfaces. For example, the Rabbit r1 device presented at CES 2024, driven by an AI operating system and LAM, brings this vision to life. It executes complex commands, leveraging GUIs with unprecedented ease. In this presentation, join me on a journey as a software engineer tinkering with WebRTC, Janus, and LLM/LAMs. Together, we’ll evaluate the current state of these AI technologies, unraveling the potential they hold for shaping the future of real-time applications.

Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications

Alberto González Trastoy

At the recent Microsoft Ignite 2023 conference, Microsoft unveiled a groundbreaking strategy that will redefine enterprise work management. The plan involves integrating Microsoft’s key planning tools, Microsoft To Do, Microsoft Planner, and Microsoft Project for the web into a unified experience called “Microsoft Planner.” What does this new strategy from Microsoft mean for current users? Join us and learn how best to take advantage of this announcement while gaining a clear path on how to elevate the current state of Microsoft Planner from a basic task manager to a comprehensive tool for Enterprise Work Management using OnePlan. Learn how OnePlan’s integration with Microsoft Planner allows for strategic alignment with business goals through advanced features like strategic planning, portfolio management, resource management, financial management, and more!

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

OnePlan Solutions

Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf

kalichargn70th171

introduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdf

VishalKumarJha10

Direct Style Effect Systems -The Print[A] Example- A Comprehension Aid

Philip Schwarz

How To Troubleshoot Collaboration Apps for the Modern Connected Worker

ThousandEyes

Azure Native Qumulo scales elastically for common High Performance Compute (HPC) workloads based on application requirements for: Financial Services, Automotive, Genomics / Life Sciences, Media and Entertainment, Energy, Oil and Gas, etc. Performance can be dialed UP (and back down) much higher than the examples shown here. These slides offer a glimpse into ANQ's HPC capabilities, although at a smaller scale. We invite YOU to do your own testing (with a free ANQ trial) and work with us to test your HPC workloads in Azure.

Azure_Native_Qumulo_High_Performance_Compute_Benchmarks.pdf

ryanfarris8

Looking for an efficient way to manage your finances? Look no further than our money management app. With easy-to-use features, you can track your expenses, create budgets, and monitor your savings goals all in one place. Our app provides real-time updates on your spending habits and helps you make smarter financial decisions. Take control of your finances today with our user-friendly money management app.

Right Money Management App For Your Financial Goals

Jhone kinadey

call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️

Delhi Call girls

Test automation is a cornerstone of software development and quality assurance in today's rapidly evolving digital landscape. Its significance cannot be overstated. Businesses can enhance efficiency, productivity, and accelerate software delivery to market through automation, streamlining testing processes effectively. This comprehensive guide addresses the best practices for test automation in 2024. It offers a detailed checklist to empower you to optimize your automation efforts and maintain a competitive edge.

The Ultimate Test Automation Guide_ Best Practices and Tips.pdf

kalichargn70th171

In the past six months, the AI landscape has undergone a massive transformation, ushering in a new era of productivity with the latest in Large Language Models (LLMs) and AI technology. This deep dive unlocks how to: Create CustomGPT Models: No coding needed to tailor AI for your unique projects. Integrate your own data, including PDFs and Excel sheets, making information handling a breeze. Plus, discover how to call your own actions/integrations for even more personalized utility. Navigate Advanced Prompting: Overcome AI's memory limits and utilize Retrieval-Augmented Generation for accessing your personalized data, streamlining how you interact with AI. Stay Ahead with AI Trends: Peek into the evolving world of LLMs, featuring newcomers like Google Gemini, Anthropic Claude, Open Sora, and Twitter Grok, and understand what their advancements mean for your productivity. Witness Real-Life Transformations: Through examples and prompt demonstrations, see firsthand how these AI strategies revolutionize routine tasks, from data analysis to content creation. Learn to leverage image output and input for advanced practical use cases, adding a new dimension to your productivity toolkit. No previous coding or AI experience is needed for this talk. Stay ahead in the fast-evolving world of work. Embrace the AI revolution and transform your workflow with advanced LLM techniques. Join us to ensure you're not left behind in the productivity race.

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

VictorSzoltysek

VTU technical seminar 8Th Sem on Scikit-learn

AmarnathKambale

Diamond Application Development Crafting Solutions with Precision

SolGuruz

Data spaces in distributed environments should be allowed to evolve in agile ways providing data space owners with large flexibility about which data they store. Agility and heterogeneity, however, jeopardize data exchanges because representations may build on varying ontologies and data consumers may not rely on the semantic correctness of their queries in the context of semantically heterogeneous, evolving data spaces. Graph data spaces are one example of a powerful model for representing and querying data whose semantics may change over time. To assert and enforce conditions on individual graph data spaces, shape languages (e.g SHACL) have been developed. We investigate the question of how querying and programming can be guarded by reasoning over SHACL constraints in a distributed setting and we sketch a picture of how a future landscape based on semantically heterogeneous data spaces might look like.

Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...

Steffen Staab

Investing in AI transformation today The modern business advantage: Uncovering deep insights with AI Organizations around the world have come to recognize AI as the transformative technology that enables them to gain real business advantage. AI’s ability to organize vast quantities of data allows those who implement it to uncover deep business insights, augment human expertise, drive operational efficiency, transform their products, and better serve their customers

Microsoft AI Transformation Partner Playbook.pdf

Willy Marroquin (WillyDevNET)

5 Signs You Need a Fashion PLM Software.pdf

Wave PLM

Software Quality Assurance Interview Questions

Arshad QA

Model Call Girl Services in Delhi reach out to us at 🔝 9953056974 🔝✔️✔️ Our agency presents a selection of young, charming call girls available for bookings at Oyo Hotels. Experience high-class escort services at pocket-friendly rates, with our female escorts exuding both beauty and a delightful personality, ready to meet your desires. Whether it's Housewives, College girls, Russian girls, Muslim girls, or any other preference, we offer a diverse range of options to cater to your tastes. We provide both in-call and out-call services for your convenience. Our in-call location in Delhi ensures cleanliness, hygiene, and 100% safety, while our out-call services offer doorstep delivery for added ease. We value your time and money, hence we kindly request pic collectors, time-passers, and bargain hunters to refrain from contacting us. Our services feature various packages at competitive rates: One shot: ₹2000/in-call, ₹5000/out-call Two shots with one girl: ₹3500/in-call, ₹6000/out-call Body to body massage with sex: ₹3000/in-call Full night for one person: ₹7000/in-call, ₹10000/out-call Full night for more than 1 person: Contact us at 🔝 9953056974 🔝. for details Operating 24/7, we serve various locations in Delhi, including Green Park, Lajpat Nagar, Saket, and Hauz Khas near metro stations. For premium call girl services in Delhi 🔝 9953056974 🔝. Thank you for considering us!

CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE

9953056974 Low Rate Call Girls In Saket, Delhi NCR

+971565801893 Mtp-Kit (500MG) Prices » Dubai [(+971565801893**)] Abortion Pills For Sale In Dubai, UAE, Mifepristone and Misoprostol Tablets Available In Dubai, UAE CONTACT DR.Leen Whatsapp +971565801893 We Have Abortion Pills / Cytotec Tablets /Mifegest Kit Available in Dubai, Sharjah, Abudhabi, Ajman, Alain, Fujairah, Ras Al Khaimah, Umm Al Quwain, UAE, Buy cytotec in Dubai +971565801893''''Abortion Pills near me DUBAI | ABU DHABI|UAE. Price of Misoprostol, Cytotec” +971565801893' Dr.DEEM ''BUY ABORTION PILLS MIFEGEST KIT, MISOPROTONE, CYTOTEC PILLS IN DUBAI, ABU DHABI,UAE'' Contact me now via What's App…… abortion Pills Cytotec also available Oman Qatar Doha Saudi Arabia Bahrain Above all, Cytotec Abortion Pills are Available In Dubai / UAE, you will be very happy to do abortion in Dubai we are providing cytotec 200mg abortion pill in Dubai, UAE. Medication abortion offers an alternative to Surgical Abortion for women in the early weeks of pregnancy. We only offer abortion pills from 1 week-6 Months. We then advise you to use surgery if its beyond 6 months. Our Abu Dhabi, Ajman, Al Ain, Dubai, Fujairah, Ras Al Khaimah (RAK), Sharjah, Umm Al Quwain (UAQ) United Arab Emirates Abortion Clinic provides the safest and most advanced techniques for providing non-surgical, medical and surgical abortion methods for early through late second trimester, including the Abortion By Pill Procedure (RU 486, Mifeprex, Mifepristone, early options French Abortion Pill), Tamoxifen, Methotrexate and Cytotec (Misoprostol). The Abu Dhabi, United Arab Emirates Abortion Clinic performs Same Day Abortion Procedure using medications that are taken on the first day of the office visit and will cause the abortion to occur generally within 4 to 6 hours (as early as 30 minutes) for patients who are 3 to 12 weeks pregnant. When Mifepristone and Misoprostol are used, 50% of patients complete in 4 to 6 hours; 75% to 80% in 12 hours; and 90% in 24 hours. We use a regimen that allows for completion without the need for surgery 99% of the time. All advanced second trimester and late term pregnancies at our Tampa clinic (17 to 24 weeks or greater) can be completed within 24 hours or less 99% of the time without the need surgery. The procedure is completed with minimal to no complications. Our Women's Health Center located in Abu Dhabi, United Arab Emirates, uses the latest medications for medical abortions (RU-486, Mifeprex, Mifegyne, Mifepristone, early options French abortion pill), Methotrexate and Cytotec (Misoprostol). The safety standards of our Abu Dhabi, United Arab Emirates Abortion Doctors remain unparalleled. They consistently maintain the lowest complication rates throughout the nation. Our Physicians and staff are always available to answer questions and care for women in one of the most difficult times in their lives. The decision to have an abortion at the Abortion Clinic in Abu Dhabi, United Arab Emirates.+971565801893

+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...

Health

Recently uploaded (20)

call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️

Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications

Introducing Microsoft’s new Enterprise Work Management (EWM) Solution

Learn the Fundamentals of XCUITest Framework_ A Beginner's Guide.pdf

introduction-to-automotive Andoid os-csimmonds-ndctechtown-2021.pdf

Direct Style Effect Systems -The Print[A] Example- A Comprehension Aid

How To Troubleshoot Collaboration Apps for the Modern Connected Worker

Azure_Native_Qumulo_High_Performance_Compute_Benchmarks.pdf

Right Money Management App For Your Financial Goals

call girls in Vaishali (Ghaziabad) 🔝 >༒8448380779 🔝 genuine Escort Service 🔝✔️✔️

The Ultimate Test Automation Guide_ Best Practices and Tips.pdf

AI Mastery 201: Elevating Your Workflow with Advanced LLM Techniques

VTU technical seminar 8Th Sem on Scikit-learn

Diamond Application Development Crafting Solutions with Precision

Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...

Microsoft AI Transformation Partner Playbook.pdf

5 Signs You Need a Fashion PLM Software.pdf

Software Quality Assurance Interview Questions

CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE

+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...

Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts

1. OMM Solutions TECHtalk #1 www.omm-solutions.de 30.03.2017 < OMM Solutions GmbH > 1 www.tech-talks.eu

2. Einmal im Monat ist TECHtalk Zeit! First come first served! < OMM Solutions GmbH > 2

3. Talk: Building an intelligent Pullup-Classifier Speaker: Olaf Horstmann 3< OMM Solutions GmbH >

4. 30.03.2017 < OMM Solutions GmbH > 4

5. • should COUNT the pullups • should detect WHO • should classify the QUALITY The Goal 30.03.2017 < OMM Solutions GmbH > 5

6. Image from: http://www.instructables.com/id/Pull-Up-Counter/ Existing solutions 30.03.2017 < OMM Solutions GmbH > 6

7. 30.03.2017 < OMM Solutions GmbH > 7

8. ✓ COUNT × WHO × QUALITY Can we use it? 30.03.2017 < OMM Solutions GmbH > 8

9. The Pressure-Sensor Iteration #1 30.03.2017 < OMM Solutions GmbH > 9

10. Let‘s try it! 30.03.2017 < OMM Solutions GmbH > 10

11. OKAY… 30.03.2017 < OMM Solutions GmbH > 11

12. The Ultrasonic-Sensor Iteration #2 30.03.2017 < OMM Solutions GmbH > 12

13. 30.03.2017 < OMM Solutions GmbH > 13

14. 30.03.2017 < OMM Solutions GmbH > 14

15. • Only works on perpendicular angles (+/-15°) • Only works on „flat“ surfaces (hair or clothes = bad) • You can hear it when it is quiet BUT… 30.03.2017 < OMM Solutions GmbH > 15

16. An optical sensor Iteration #3 30.03.2017 < OMM Solutions GmbH > 16

17. 30.03.2017 < OMM Solutions GmbH > 17

18. 30.03.2017 < OMM Solutions GmbH > 18

19. Success 30.03.2017 < OMM Solutions GmbH > 19

20. • Cost more than the other sensors • Inaccurate/slow > 2m • Might not work very well in direct sunlight (did not test) Any Drawbacks? 30.03.2017 < OMM Solutions GmbH > 20

21. • Collected data from different people • Prepate the data • Implement an AI to classify the data Now what? 30.03.2017 < OMM Solutions GmbH > 21

22. Collecting/Comparing Data 30.03.2017 < OMM Solutions GmbH > 22

23. • Algorithm to detect individual pullups (=> count) • Label each data-set manually (=> who & quality) Data-Preparation 30.03.2017 < OMM Solutions GmbH > 23

24. Data-Preparation 30.03.2017 < OMM Solutions GmbH > 24

25. • Throw in the raw data (~200 pullups) • Train it • See what happens • => accuracy ~60% With Tensorflow AI Iteration #1 30.03.2017 < OMM Solutions GmbH > 25

26. • More data (a lot more!) • Adjust the network (not really better) • Use meta-data instead of raw data How can we improve this? 30.03.2017 < OMM Solutions GmbH > 26

27. • Using ~15 different meta-data-points • => accuracy ~85% AI Iteration #2 30.03.2017 < OMM Solutions GmbH > 27

28. • Normalize data (high values are bad!) • …and more data! …but there‘s still room for improvements It‘s Okay… 30.03.2017 < OMM Solutions GmbH > 28

29. • Normalized data • => accuracy at +90% AI Iteration #3 30.03.2017 < OMM Solutions GmbH > 29

30. „The Product“ 30.03.2017 < OMM Solutions GmbH > 30

31. • Data preparation is probably the most important step • Visualizing the data helps analyzing it • Less data can be compensated by transforming the data first • Having more classes can help with the accuracy of the whole model • More data is always better Learnings 30.03.2017 < OMM Solutions GmbH > 31

32. Vielen Dank für Eure Aufmerksamkeit! 32< OMM Solutions GmbH >

33. Ihr persönlicher Ansprechpartner Fragen oder Interesse? < OMM Solutions GmbH > 33 Olaf Horstmann Technology & Innovation OMM Solutions GmbH Vor dem Lauch 4 70567 Stuttgart Germany oh@omm-solutions.de +49 (0)711 75 86 46 04

34. 34< OMM Solutions GmbH > www.omm-solutions.de OMM Solutions GmbH Vor dem Lauch 4 70567 Stuttgart Geschäftsführer Martin Allmendinger Malte Horstmann Olaf Horstmann Kontakt Telefon: +49 711 6747 051-0 E-Mail: info@omm-solutions.de Umsatzsteuer-ID: DE295716572 Sitz der Gesellschaft: Stuttgart Amtsgericht Stuttgart, HRB 749562 Impressum

Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts

Recommended

Recommended

More Related Content

Similar to Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts

Similar to Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts (15)

More from OMM Solutions GmbH

More from OMM Solutions GmbH (20)

Recently uploaded

Recently uploaded (20)

Building an intelligent Pullup-Classifier - Iterations, Learnings, Thoughts