ML in PL - The Largest Machine Learning Conference in Poland

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It's been a big year for AI and Machine Learning. The data science ecosystem is maturing, and with it has come company creations, filling market niches, increased grant opportunities, and a culture of innovation. Machine Learning has become a catalyst for change, accelerating product development, mitigating environmental damages, and driving profitability. And leading this front is ML in PL, the largest Machine Learning conference in Poland. <ul><li><a href="#anchor-1" rel="noopener noreferrer">What is ML in PL?</a></li><li><a href="#anchor-2" rel="noopener noreferrer">Register Now</a></li><li><a href="#anchor-2" rel="noopener noreferrer">Keynote Speakers</a></li><li><a href="#anchor-3" rel="noopener noreferrer">Appsilon's Sponsored Talk</a></li><li><a href="#anchor-4" rel="noopener noreferrer">Conclusion</a></li></ul> <h2 id="anchor-1">What is ML in PL?</h2> <a href="https://mlinpl.org/" target="_blank" rel="noopener noreferrer">ML in PL</a> is a non-profit organization that promotes research-oriented machine learning through the ML in PL conference. In past years, ML in PL conference was held in Poland and attracted speakers conducting ML research at companies like Deepmind, Google, Microsoft, and NVIDIA, as well as universities such as Oxford and NYU. The conference serves as a tool for ML in PL to engage the international ML community. Connecting academic researchers, students, and professionals for a 3-day event. Over the years, the growing demand for participation has bolstered ML in PL's efforts in finding high-caliber speakers and reaching a larger audience. <blockquote><strong><a href="https://appsilon.com/pp-yolo-object-detection/" target="_blank" rel="noopener noreferrer">PP-YOLO</a> - How does this object detection framework work and is it faster than YOLOv4?</strong></blockquote> In the past year, ML in PL has shifted to an online platform. Participants can view lectures and visit sponsors' booths (like Appsilon!). During the event, participants and contributors can network via Gather Town. An immersive, online space that gives a little more life to the virtual world of e-conferences. <h3>When is it?</h3> The Machine Learning conference takes place <strong>November 5th-7th</strong>. Now that ML in PL is online, participants can join from across the globe. Whether at home or on the go, it's a perfect opportunity to explore what's happening in ML research. If you haven't attended ML in PL before, now is the time. Don't miss out! <h3 id="anchor-2">Register Now</h3> Although early bird registration has passed, conference seats are still available. Be sure to purchase your tickets at the <a href="https://conference2021.mlinpl.org/" target="_blank" rel="noopener noreferrer">2021 conference site</a>. You don't want to miss the opportunity to hear from the Keynote speakers and network within one of the largest Machine Learning conferences in 2021. <h3>Keynote Speakers at the Machine Learning conference</h3> The Keynote speakers of this year's event are a truly impressive line-up of experts and leaders in the field of AI. This year's list includes: <strong>Daphne Koller</strong> is the CEO and Founder of Insitro and former co-CEO of Coursera. Among Daphne's long list of achievements includes the Rajeev Motwani Professor of Computer Science at Stanford, one of TIME Magazine's 100 most influential people of 2012, and a fellow of the American Association for Artificial Intelligence, American Academy of Arts and Sciences, and International Society of Computational Biology. <strong>Yoshua Bengio</strong> is a world leader in AI and deep learning. He currently serves as a Full Professor Université de Montreal and is the Founder and Scientific Director of Mila and IVADO. Yoshua is the co-recipient of the Turing Award and a Fellow of the Royal Society of London and Canada. <strong>Rich Caruana</strong> is a Senior Principal Research at Microsoft. Rich is the recipient of an NSF Career Award for Meta Clustering. Before Microsoft, Rich was a faculty member for Cornell, UCLA's Medical School, and CMU's Center for Learning and Discovery. <strong>Lukasz Kaiser</strong> is the co-author of the TensorFlow system, as well as the Tensor2Tensor and Trax libraries. He is also the co-inventor of  Transformers - a type of neural network architecture. <h3 id="anchor-4">Sponsored Talk</h3> Mbaza - by ML Lead Jędrzej Świeżewski Mbaza is an open-source application using machine learning to aid wildlife protection. It is currently being used by park rangers and bio-conservationists in Gabon and tested in other countries. <blockquote><strong>Appsilon ML Lead Jędrzej Świeżewski Co-authors research on applying <a href="https://www.biorxiv.org/content/10.1101/2020.09.12.294538v1" target="_blank" rel="noopener noreferrer">Machine Learning models to automate ecological inference</a>.</strong></blockquote> During the presentation, I will highlight some of the challenges we needed to overcome when creating Mbaza, with a particular focus on building the machine learning model, but also on the peculiarities of building an application that needs to operate in the wild (the second-largest tropical rainforest in the World). <blockquote><strong>Are Computer Vision models vulnerable to <a href="https://appsilon.com/weight-poisoning-computer-vision/" target="_blank" rel="noopener noreferrer">weight-poisoning attacks</a>?</strong></blockquote> The presentation will involve magnificent photos of wildlife taken in Central Africa and used for the training and evaluation of our models. <img class="aligncenter wp-image-8645 size-medium" src="https://wordpress.appsilon.com/wp-content/uploads/2021/10/Jędrzej-Świeżewski-364x500.png" alt="Jędrzej Świeżewski avatar and title" width="364" height="500" /> <h3>About Jędrzej Świeżewski, PhD</h3> Dr. Jędrzej Świeżewski is the Machine Learning Lead at Appsilon. He has contributed to numerous ML and Computer Vision projects and is an avid supporter of the Data For Good initiative. Jędrzej holds a PhD in theoretical physics, focusing on classical and quantum gravity. You can find more on <a href="http://inspirehep.net/search?ln=en&amp;p=author%3AJedrzej.Swiezewski.1%20AND%20collection%3Apublished" target="_blank" rel="noopener noreferrer">his research on inSPIRE</a>. <h2>Appsilon at Poland's largest Machine Learning conference</h2> Appsilon is a data science company that builds the world's most advanced enterprise R Shiny applications and delivers custom ML solutions. Fortune 500 companies trust Appsilon to develop custom Shiny apps, scale PoCs, improve Shiny app performance, and enhance dashboard UI. Our ML team has leveraged ML and Computer Vision to help real-time poaching mitigation, natural disaster damage assessments and recovery, genetic research, and automatic defect detection in consumer products.  <blockquote><strong>AI and disaster risk management. See how Appsilon's helped build a <a href="https://appsilon.com/ai4g-a-decision-support-system-for-disaster-risk-management-in-madagascar/" target="_blank" rel="noopener noreferrer">decision support system in Madagascar</a>. </strong></blockquote> What sets Appsilon apart from other technology companies is our commitment to make a difference and use Data for Good. R Shiny developers, data scientists, and ML experts work in Appsilon with a common goal: advance technology to preserve and improve human life. Apart from being a one-stop shop for R Shiny development, Appsilon is a contributor to the R community. Thousands of data-driven companies, R&D labs, academic institutions, and state departments use Appsilon’s open source Shiny packages in their data science projects. That is why we support organizations and events like ML in PL. <h2 id="anchor-5">Conclusion</h2> As data science professionals and active contributors to the data science community, we value the knowledge shared and the connections made at events like ML in PL. We believe it's important to foster the data science community by promoting opportunities to connect and disseminate state-of-the-art research. That's why we're proud to sponsor ML in PL's Machine Learning conference. We look forward to hearing new discoveries and hope to help inspire the next generation of ML leaders.

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