Machine learning is and should not be the exclusive domain of large commercial companies, data scientists, mathematics, computer scientists or hackers. Our belief is that every business and everyone should be able to take advantage of the machine learning techniques and applications available.
This document provides an introduction to machine learning, including definitions of key related concepts like artificial intelligence, machine learning, and deep learning. It discusses machine learning applications in industry, such as quality control, forecasting, chatbots, and sentiment analysis. It also offers two approaches to starting in machine learning: starting from programming and frameworks then moving to math, or starting from the math then moving to programming. Recommended tools include Python, Pandas, Scikit-learn, and TensorFlow. The document concludes with advice on how to start a career in machine learning engineering.
Future of data science as a professionJose Quesada
How can you thrive in a future where machine learning has been popular for a few years already?
In this talk, I will give you actionable advice from my experience training serious data scientists at our retreat center in Berlin. You are going to face these pointy, hard questions:
- What is the promise of machine learning? Has it happened yet?
- Is it easy to take advance of machine learning, now that most algorithms are nicely packaged in APIs and libraries?
- How much time should I spend getting good at machine learning? Am I good enough now?
- Are data scientists going to be replaced by algorithms? Are we all?
- Is it easy to hire talent in machine learning after the explosion of MOOCs?
Here are the key steps to understand and install common Python packages for machine learning:
1. NumPy: NumPy is the fundamental package for scientific computing in Python. It provides multidimensional array and matrix data structures along with tools to work with these data structures.
2. SciPy: SciPy builds on NumPy and provides routines for integration, optimization, linear algebra, Fourier transforms, and more. SciPy contains modules for signals and image processing, optimization, special functions, clustering, and more.
3. scikit-learn: Scikit-learn is a powerful machine learning library that supports supervised and unsupervised learning. It features various classification, regression and clustering algorithms.
4. Matplotlib: Matplotlib is a
The document discusses machine learning and how it can be used by SEOs. It defines machine learning and provides examples of applications like spam filtering, product recommendations, and home price predictions. The document encourages readers to think of problems machine learning could solve using available data and models. Specific opportunities for SEOs are discussed, like predicting customer churn, title tag optimization, and log file analysis. Readers are provided resources for learning machine learning.
Why do most machine learning projects never make it to productionCameron Vetter
Cameron Vetter discusses common mistakes made in machine learning projects that prevent them from making it into production. Some key issues include a lack of leadership support and poorly defined goals, data science teams focusing only on model creation without ensuring it is production-ready, choosing overly complex projects instead of starting simple, having the wrong team composition without the needed roles, and not establishing proper processes around software development lifecycles, testing, and monitoring of models once in production. The presentation provides advice on how to address these problems such as gaining business buy-in, taking an iterative approach, evaluating existing solutions, and having the right team and processes in place.
Using Neo4j and Machine Learning to Create a Decision Engine, CluedInNeo4j
This document discusses taking the "magic" out of machine learning by using a practical approach with Neo4j and machine learning techniques. It describes building a decision engine with Neo4j that can learn from its decisions over time using unsupervised neural networks and pattern matching combined with statistical models. While machine learning techniques are good at solving certain problems, the document advocates that the simple idea of having a weighted decision engine that can persist graph decisions asynchronously can get very far without needing to be super fast or real-time.
This document provides guidance on building a career in AI through three key steps: learning foundational skills, working on projects, and finding a job. It discusses each step in detail with chapters focused on learning technical skills, scoping AI projects, and using projects to complement career goals. The overall message is that an AI career requires lifelong learning, gaining experience through meaningful projects, and navigating an evolving job market. Building a supportive community is also important for support throughout the career journey.
*Uses of AI and data science can be found in almost any situation that produces data
* More uses for custom AI applications and data-derived
insights than for traditional software engineering
* Literacy in AI-oriented coding will be more valuable than traditional coding
This document discusses artificial intelligence, machine learning, deep learning, and data science. It defines each term and explains the relationships between them. AI is the overarching field, while machine learning and deep learning are subsets of AI. Machine learning allows machines to improve performance over time without human intervention by learning from examples, and deep learning uses artificial neural networks with many layers to closely mimic the human brain. The document provides an example of a fruit detection system using deep learning that trains a neural network to detect ripe fruit for automated harvesting.
Machine Learning is a fascinating field that has been making headlines for its incredible advancements in recent years. Whether you're a tech enthusiast or just curious about how machines can learn, this article will provide you with a simple and easy-to-understand overview of some key Machine Learning concepts. Think of it as your first step towards a Machine Learning Complete Course!
APTRON is the perfect place to learn about Machine Learning Institute in Delhi. With experienced trainers, practical training, and industry-standard resources, students can be sure that they are getting the best education possible. So, if you are looking to jumpstart your career in machine learning, APTRON is the right choice for you.
https://bit.ly/3nBAGF8
Machine Learning: Need of Machine Learning, Its Challenges and its ApplicationsArpana Awasthi
BCA Department of JIMS Vasant Kunj-II is one of the best BCA colleges in Delhi NCR. The curriculum is well updated and the subjects included all the latest technologies which are in demand.
JIMS BCA course teaches Python to II semester students and Artificial Intelligence Using Python to Sixth Semester students.
Here is a small article on the Future of Machine Learning, hope you will find it useful.
Machine Learning is a field of Computer science in which computer systems are able to learn from past experiences, examples, environments. With help of various Machine Learning Algorithms, Computers are provided with the ability to sense the data and produce some relevant results.
Machine learning Algorithms provide the technique of predicting the future outcomes or classifying information from the given input to the Machines so that the appropriate decisions can be taken.
AI and ML for Product Management by Smartsheet Sr Dir of PMProduct School
Product Management Event at #ProductCon Seattle on AI and ML for Product Management by Nitin Bhat, Senior Director of Product Management at Smartsheet.
Looking to change fields and get into tech, but don’t know what skills you need to launch your career? Maximize your marketability by pursuing tech skills in demand for the future!
This document provides an introduction to machine learning fundamentals. It defines machine learning as giving computers the ability to learn from data rather than being explicitly programmed. The document discusses the differences between artificial intelligence, machine learning, deep learning, and data science. It also covers applications of machine learning, when to use and not use machine learning, and types of machine learning problems and workflows.
Recent Advances in Machine Learning: Bringing a New Level of Intelligence to ...Brocade
Presentation by Brocade Chief Scientist and Fellow, David Meyer, given at Orange Gardens July 2016. What is Machine Learning and what is all the excitement about?
An associated blog is available here: http://community.brocade.com/t5/CTO-Corner/Networking-Meets-Artificial-Intelligence-A-Glimpse-into-the-Very/ba-p/88196
NLP & Machine Learning - An Introductory Talk Vijay Ganti
An Introductory talk with the goal of getting people started on the NLP/ML journey. A practitioner's perspective. Code that makes it real and accessible.
The document discusses machine learning and what is needed to build machine learning products. It begins with an introduction to machine learning, defining it as a computer program that improves at tasks through experience with data. It emphasizes that machine learning involves data collection, data pipelines, and measuring model performance. The key takeaways are that building machine learning products requires planning, experimenting in an iterative process, and using various machine learning frameworks and libraries while continuing to learn through online courses and communities.
How to use Artificial Intelligence with Python? EdurekaEdureka!
YouTube Link: https://youtu.be/7O60HOZRLng
* Machine Learning Engineer Masters Program: https://www.edureka.co/masters-program/machine-learning-engineer-training *
This Edureka PPT on "Artificial Intelligence With Python" will provide you with a comprehensive and detailed knowledge of Artificial Intelligence concepts with hands-on examples.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
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LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Radical open innovation requires systems thinking and problem solving methods. It involves collaboration across diverse partners to solve complex problems accelerated by technological, economic, and environmental changes. Systems thinking views problems holistically rather than through generalizations and can help address unintended consequences and design effective policies for managing systems. Key tools for systems thinking include causal loop diagrams, stock and flow models, and identifying archetypes to predict system behaviors and assess how proposed changes may impact the system over time. Simulation is also essential to validate if changes will lead to sustainable outcomes.
Radical Open Innovation - Openness by default to solve the most challenging problems!
create value within complex open innovation networks
Increase the opportunities to be ask for joining an real open innovation project.
Soliciting Ideas and search for collaborators for your open innovation project on our Real Open Innovation platform site.
Be part of a vibrant open community that strives for value creation in a sustainable way.
Free and Open Business IT Innovation: An overview of IT trends for 2017Maikel Mardjan
Businesses innovate faster using IT innovations. Faster innovation cycles are enabled by innovations in software, hardware and business science. Without business IT innovation our world would not be what it is today. Working in the IT industry means you need continuously keep up your knowledge up to date.
This report will help you and give you a head start for 2017! This report covers important business IT innovations for 2017. All open. All FOSS!
Open Architectures do not work: The need for real open ArchitecturesMaikel Mardjan
Slides of presentation given at T-dose.org 2016.
IT Architecture is not by definition high level and sometimes relevant details are of the utmost importance. Many proprietary tools exist for creating IT architectures. FOSS tools for creating architectures are still not commonly used. Also many architectures created are never exposed. In this way it is hard to learn from others. Maybe it is now time to promote open architectures. Maybe we should create more and better FOSS tools like microservices that helps us with creating the perfect FOSS architecture tool!
Slides as presented on t-dose.org (2016). This story is all about:
- System Dynamics and
- InsightMaker.com
This talk will explain the basics of system dynamics and explain how easy it is for you to use a Jupyter Notebook, InsightMaker and other FOSS tools to solve your business IT problems.
Organisaties krijgen in toenemende mate te maken met nog meer complexiteit en dynamiek. Oorzaken zijn mondialisering, nieuwe IT ontwikkelingen, nieuwe samenwerkingsvormen en het verder vervagen van grenzen tussen organisaties en hun omgeving. Deze nieuwe dynamiek en complexiteit vormen een serieuze uitdaging voor het ontwerpen en implementeren van informatiesystemen.
Systeemdynamica helpt bij beheersen van complexiteit!
Nieuwe architectuurconcepten op gebied van beveiliging kunnen als aanjager werken voor het versneld realiseren van nieuwe producten en diensten, zonder daarbij tegengehouden te worden door verstikkende beveiligingsprincipes uit het verleden.
Een bedrijfsarchitectuur of IT architectuur levert niet altijd direct voordeel. Om uit de crisis te komen of te blijven wordt een digitale architectuur belangrijker dan ooit.
Deze presentatie gaat in op wat architectuur is, hoe korte en lange termijn voordeel gehaald kan worden met architectuur en wat de valkuilen zijn in een architectuurtraject.
This document summarizes open source business models in 2010. It finds that while the number of successful open source business models is limited, companies and individuals can embrace models like donations, paid support, dual licensing or advertising. Crucial factors for success include choosing an open source license, organizing the community, and facilitating rather than controlling community contributions. The foundation BM-Support provides innovation services and networks to help companies solve problems using open source.
Business disadvantages using cloud computing exist. This report summary outlines the most important need to know disadvantages related to using cloud computing.
Discover who your target audience is and reach themQuibble
This presentation goes through a number of elements you need to consider when going through the process of identifying your target audience in order to enable to you be able to reach them and sell to them. I go through the importance of customer profiling, along with a number of ways you can discover what they really want, and where they are.
Game Product Manager VS Product Manager.pdfshohreesmaili1
Hi guys!
To do the first things first, I have to introduce myself and my background, and we need an explanation for the reason and incentive behind this summary presentation and the series of articles that may follow for more details. I am a game designer with a focus on economy design. After some years of working in game design, I felt the most inspiring thing for me is seeing an increase in a graph (of course, not the churn graph). The combination of this with a focus on features and their results and the needs of the game led me toward becoming a product manager.
At first, I started reading about product managers' roles, responsibilities, daily routines, and most importantly, the methods they use for fulfilling their responsibilities. Initially, I tried to implement these methods in our structure, but the deeper I delved into gaming product management, the more methods I found that needed to change to achieve the best results. After some time, I realized that having knowledge of how product managers in application products operate is necessary but not sufficient to call oneself a game product manager.
Of course, they invented the wheel, special thanks to them, but the fact is that we do not have a car; we have bicycles or airplanes! So, the same wheel does not work for us! In this series of articles, I want to describe how things are different when playing the role of a PM or GPM, what you need to know, and what are not our primary challenges. How to become a GPM after discussing the pros and cons of being a PM or GPM. If you are going to choose between one of them, you can stop reading this and choose PM! But if you are passionate about becoming a GPM, I suggest you read these, then take a deep breath, make your final decision, take your sword, and be ready to face dragons, without knowing how to use the sword!
In the high speed and serious universe of worldwide business, having the right administration group is fundamental for progress. International executive recruiters representatives assume an imperative part in assisting organizations with recognizing, draw in, and hold top leader ability for their worldwide development endeavors. Their profound comprehension of worldwide business sectors, broad organizations, and skill in cross-line enlistment guarantee that organizations can with certainty explore the intricacies of global employing and construct major areas of strength for a group that drives manageable development and achievement.
Research Methodology, Objectives, Types and Significance of Researchindumathi967565
Research methodology refers to the systematic, theoretical analysis of the methods applied to a field of study. It comprises the theoretical analysis of the body of methods and principles associated with a branch of knowledge. research is integral to every aspect of business operations. It supports informed decision-making, identifies opportunities and threats, enhances customer understanding, improves efficiency, fosters innovation, aids in strategic planning, refines marketing strategies, manages risk, boosts employee satisfaction, enhances financial performance, and informs policy formulation. This comprehensive understanding and application of research allow businesses to operate more effectively and sustainably in a competitive environment. Research methodology refers to the systematic, theoretical analysis of the methods applied to a field of study. It encompasses the principles, procedures, and techniques used by researchers to collect, analyze, and interpret data. Essentially, research methodology provides the blueprint for the entire research process, ensuring that the study is carried out in a structured, reliable, and valid manner.
Travel Tech Pitch Deck | ByeByeCity,com - Short Breaks Discovery & Booking Pl...Rajesh Math
ByeByeCity.com is a platform where users can discover and book short breaks by using the only web booking engine in India which uses advanced algorithms to sell Non-Standardised Travel Inventories. It is aggregating a fragmented market to build the long tail of the Travel Market.
How AI is Disrupting Service Industry More Than Design ThinkingBody of Knowledge
Artificial Intelligence (AI) and Design Thinking are two powerful tools that, when used together, can revolutionize the service industry. By combining these approaches, businesses can develop innovative solutions that enhance customer experience, increase efficiency, and drive growth. Here's how AI and Design Thinking are disrupting the service industry
Innovative Full Stack Developer Crafting Seamless Web SolutionsHarwinder Singh
As an innovative full stack developer, I specialize in creating complete web solutions from front-end design to back-end functionality. With expertise in HTML, CSS, JavaScript, and server-side technologies like Node.js and Python, I build scalable, responsive, and user-friendly applications. My focus is on delivering high-quality, efficient, and impactful digital experiences.
Christmas Decorations_ A Guide to Small Christmas Trees, Candle Centerpieces,...Lynch Creek Farm
Transform your home into a festive wonderland this Christmas with our guide to small Christmas trees, elegant candle centerpieces, and unique wreaths for your front door. Discover the perfect small Christmas tree for limited spaces, learn how to create stunning candle centerpieces, and find the best unique wreaths for your front door to welcome guests. Embrace sustainable decorating ideas, personalize your decor, and achieve a cohesive holiday look that spreads joy throughout your home.
TPH Global Solutions Overview: Successful Strategies for Selling to Mass Merc...David Schmidt
TPH Global Solutions makes it easy to get your products to market, through the maze of retailer requirements and complex supply chain challenges that include missed deliveries, packaging errors, and shipping damage.
From pitch to profits, TPH delivers successful retail merchandising campaigns with custom point of purchase (POP) displays and custom packaging that meet the toughest demands of retailer buyers and customers at Costco, Sam’s Club, BJ’s, Walmart, Home Depot, Lowe’s, Walgreens, CVS, Kroger, Meijer, Petco, and more.
If you’re an established brand needing to take the pain out of your supply chain, TPH ensures global, on-time and on-budget delivery so you can focus on making great products instead of dealing with headaches.
If you’re an emerging brand needing to convert new retail opportunities, TPH will help you land and pass the test order – we know all major retailer requirements and provides you with total cost visibility, so you will negotiate with confidence and fly through the toughest approval process.
With deep expertise in retailer requirements and global supply chain management, we deliver confidence for brand managers – since 1965.
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ConvertKit: Best Email Marketing Tool for 2024Rakesh Jalan
Front Slide
ConvertKit: Best Email Marketing Tool for 2024
Next Slide
What is Email Marketing?
Email marketing involves promoting products or services via email to potential customers. Tools like ConvertKit enhance the effectiveness of email marketing by helping you reach your target audience and elevate your business.
Next Slide
What is ConvertKit?
ConvertKit is a top email marketing tool, favored by content creators and small businesses. It offers features like automation, landing pages, sequencing, and broadcasting, making it ideal for generating and converting leads efficiently.
Next Slide
Key Features of ConvertKit
1. Landing Pages: Easily create customizable landing pages.
2. Forms: Embed forms on your website to generate leads.
3. Automation: Automate email responses with pre-built templates.
4. Broadcasting: Send personalized emails to thousands of subscribers.
Next Slide
Key Features of ConvertKit
5. Sequencing: Automate email series to convert leads into customers.
6. Integration: Integrate with platforms like affiliate sites and e-commerce.
7. Commerce: Start an e-commerce business without a website.
8. Creator Pro: Advanced features for selling high-cost products.
Next Slide
How ConvertKit Can Help Your Business Grow
1. Convert Casual Visitors: Turn social media followers into subscribers.
2. Build Relationships: Customize emails to build strong audience relationships.
3. Source of Earnings: Use trust to convert subscribers into sales.
Next Slide
Join ConvertKit Affiliate Program
ConvertKit's affiliate program offers free training, premium tools, and a 30% commission for referrals.
Next Slide
ConvertKit Pricing Plans
ConvertKit has Monthly and Yearly plans with Free, Creator, and Creator Pro tiers. Start with the free plan and upgrade as needed.
Next Slide
ConvertKit Alternatives
1. Mailchimp: All-in-one marketing platform.
2. GetResponse: Focus on landing pages and email lists.
3. ActiveCampaign: Advanced follow-up sequences.
4. AWeber: Building mailing lists and designing newsletters.
Next Slide
ConvertKit vs. Mailchimp
- Automation: ConvertKit offers advanced options.
- Landing Pages: ConvertKit has more templates.
- Customer Support: ConvertKit offers 24/7 support in all plans.
- Email Sending Limit: ConvertKit allows unlimited emails.
- Migration: ConvertKit offers free migration services.
Next Slide
ConvertKit vs. GetResponse
- Simplicity: ConvertKit is user-friendly for small businesses.
- Sequencing: Easier to use in ConvertKit.
- WordPress Plugin: Available in ConvertKit.
- Charges: No charges for duplicate signups in ConvertKit.
Next Slide
Conclusion
Email marketing is an excellent method to showcase your business and sell high-value products. ConvertKit is a robust tool to help you reach your target audience and start earning.
4. WHOAMI
Name : Maikel Mardjan
▪ Architecture & Design
▪ 24+ years working within IT Industry
▪ Master (MSc) Business Studies of
University of Groningen
▪ Master degree (MSc) Electrical
Engineering, of Delft University of
Technology
▪ …and still likes to do real hands-on
programming (C/C++, Java, Python,
PHP,JS,GOlang etc) to make and
break things
I love solving IT challenges and creating
designs for complex systems.
@maikelmardjan
5. AGENDA
▪ What is Machine Learning
▪ How does machine learning work (Simplified)
▪ What is Free and Open
▪ Problems and challenges for Free and Open Machine Learning
7. WHAT IS MACHINE LEARNING?
In essence machine learning makes computers learn the
same way people learn:
▪ Through experience.
And just as with humans algorithms exist that makes it
possible to make use of learned experience of other
computers.
8. WHAT IS MACHINE LEARNING?
Machine Learning can be defined as:
▪ A field of computer science that uses statistical
techniques to give computer systems the ability to
“learn”.
So progressively improve performance on a specific task
using data, without being explicitly programmed.
9. AI, ML AND DEEP LEARNING
Artificial Intelligence
Machine Learning
Deep Learning
15. EXAMPLE APPLICATIONS OF ML
▪ Quality inspection and improvement
▪ Vision (E.g. Face detection, Object Detection, Image
classification)V
▪ Security (Fraud detection, Surveillance, Spam filters, Network
Intrusion Detection)
16. AGENDA
▪ What is Machine Learning
▪ How does machine learning work (Simplified)
▪ What is Free and Open
▪ Problems and challenges for Free and Open Machine Learning
17. THE PARADIGM SHIFT: CREATING SMART
SOFTWARE
Traditional programming vs Machine Learning
Computer
(‘Traditional programming’)
Input Create Program
Output
18. THE PARADIGM SHIFT: CREATING SMART
SOFTWARE
Traditional programming vs Machine Learning
Computer
(Machine Learning)
Input Output
Learning
program
New
input
New
Output
19. SO IT IS NOT PROGRAMMING…
With ML you can create (‘program’) a cat detector by providing your
machine learning system many examples of cats and dogs.
cat cat dog dog
The more cats you feed your ML algorithm, the better your outcome
will be!
cat
dogdog
cat
20. MUST HAVE FOR ML
For machine learning, four things are needed:
▪ Data. More is better.
▪ A model of how to transform the data.
▪ A ‘loss function’ to measure how good the model is
performing.
▪ An algorithm to tweak the model parameters such that the
loss function is minimized
21. DATA FOR MACHINE LEARNING
▪ Images
▪ Text
▪ Video
▪ Structured data (E.g. Webpages, electronic medical records,
car, electricity bills, etc.)
More = Better
22. ML WORKING: IT CAN BE SUPER COMPLEX…
Machine Learning
Supervised
task driven
(Regression /
Classification)
Unsupervised
Data Driven
(Clustering)
Reinforcement
(Algorithms
learning from
environment)
23. NEURAL NETWORKS (NNS)
Neural networks (NNs) can be defined as:
▪ Algorithms in machine learning that are implemented by using
the structure of neural networks.
Neural networks model the data using artificial neurons. So Neural
networks thus mimic the functioning of the human brain.
A brain’s neural networks continuously change and update
themselves in many ways. This happens as a direct result of
learning and experience.
26. KNOWLEDGE
Defining knowledge is hard, but crucial for many machine learning
applications. An attempt to define knowledge in the context of ML:
▪ The ability of a computer to reason by understanding the
relationship between people, things, places, events and
context.
27. AGENDA
▪ What is Machine Learning
▪ How does machine learning work (Simplified)
▪ What is Free and Open
▪ Problems and challenges for Free and Open Machine Learning
34. AGENDA
▪ What is Machine Learning
▪ How does machine learning work (Simplified)
▪ What is Free and Open
▪ Problems and challenges for Free and Open Machine Learning
36. PROBLEMS AND CHALLENGES FOR FREE AND
OPEN MACHINE LEARNING
• Open science
• Open data
• Open access
• Open research
• Open Source Software
• Culture
• Change
• Commercial interest
• Economics
• Knowledge
• Awareness
37. THE BASE WORK WITH MACHINE LEARNING
Important
Interesting
Who Cares?
Is ML really needed?
Is anyone interested at all?
If it is not important, not
interesting and delivers no
value: Do not do it!
Exploratory
Fundamentally interesting
problems.
Machine learning Could help
to solve it.
Find people who like to play
with this problem.
Shit Work
Crucial for doing the crucial
problem solving work with ML.
A good fundament based on a solid
architecture, infrastructure,
development pipeline will always
deliver value later.
High Value
Applying ML delivers value.
Professionals and companies like
interesting & important projects
when developing applications
using ML.
38. SUMMARY AND RECAP
▪ What is Machine Learning
▪ How does machine learning work (Simplified)
▪ What is Free and Open
▪ Problems and challenges for Free and Open Machine Learning
39. THANK YOU!
Support Free and Open Machine Learning
Contribute to “Free and Open Machine Learning Book”
Check on: https://www.bm-support.org/projects/
More information?
Call me : +31 [0] 6 22869536 of
Mail : info@organisatieontwerp.nl
Twitter : @maikelmardjan
Also available for solving
your real nasty complex IT problems!
https://nocomplexity.com/
40. ABOUT BM-SUPPORT.ORG
The Business Management Support Foundation is a not for profit
organization for radical open business innovation.
The purpose of the foundation is to stimulate and perform research
and development on the broad field of system sciences and practical
applications. We do this by creating open innovation networks
with other non profit organizations and profit organizations.
The BM-Support.org foundation is devoted to the interdisciplinary
inquiry into the nature of complex systems.
The foundation is created in 2007 to support research and
development of innovation projects.
Check https://www.bm-support.org for more information!