Machine Learning Cafe
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16 episodes
In this episode, our guest was Balázs Kégl who is head of AI Research at Huawei Paris. We were talking about machine learning projects from the organizational point of view. We talked about the relationship between technical and non-technical people, and why are there so many POC projects why only a few of them is productionised? So, if you are a data scientist and you cannot convince your manager or your client to create a project, you should definitely listen to this episode. Moreover, we talked about some technical stuff at the end. Connect Balazs at Linkedin: https://www.linkedin.com/in/balazskegl/ ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
We continue with a micro-series, where we talk about alternative learning methods. In the first episode of this micro-series our guest is Dmitry Krotov, Researcher at MIT-IBM Watson AI Lab and IBM Research in Cambridge. Among many things, we will talk about an unusual learning rule, which has a degree of biological plausibility. Find Dmitry on Linkedin: https://www.linkedin.com/in/krotovdmitry/ Paper: Unsupervised Learning by Competing Hidden Units https://arxiv.org/abs/1806.10181 Paper: Local Unsupervised Learning for Image Analysis: https://arxiv.org/abs/1908.08993 ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this "extra" episode, our guest is Denis Rothman, who is an Artificial Intelligence Specialist. He has spent 40 years in this industry, he is the author of the book called "Artificial Intelligence by Example". He is a teacher, a speaker, and he is an exceptional expert. He has a very special view on what software development is and how to build-up systems that may or may not use artificial intelligence. We believe he is one of the brightest minds we have ever talked to. I think if you listen to this episode you will have new viewpoints of the world. LinkedIn: https://www.linkedin.com/in/denis-rothman-0b034043/ Latest Book: https://www.amazon.com/Artificial-Intelligence-Example-advanced-learning/dp/1839211539/ref=sr_1_1?dchild=1&keywords=Artificial+Intelligence+by+Example&qid=1591873875&sr=8-1 ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode, our guest was Vladimir Vlasov, who is a senior machine learning researcher at Rasa. If you don't know Rasa, it's a company that is building a standard infrastructure for conversational AI. Vladimir is working on Rasa's machine learning-based dialogue tools which allow developers to automate contextual conversations. So we were talking about state-of-the-art area of conversational AI and NLP, also briefly how Rasa’s framework is built up, and what are the technical problems to be solved, and what is the future of conversational AI. Vladimir on LinkedIn: https://www.linkedin.com/in/vladimir-vv-vlasov/ Rasa: https://rasa.com/ Conference on 18th June: https://www.l3-ai.dev YouTube channel: https://www.youtube.com/channel/UCJ0V6493mLvqdiVwOKWBODQ Algorithm Whiteboard: https://www.youtube.com/watch?v=wWNMST6t1TA&list=PL75e0qA87dlG-za8eLI6t0_Pbxafk-cxb Using Neural Networks to Find Answers in Tables: https://ai.googleblog.com/2020/04/using-neural-networks-to-find-answers.html ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode, our guest is Eugene Dubossarsky, who is the chief data scientist at AlphaZetta and co-founder at multiple data science companies in Australia. He is a managing partner of the Global Training Academy and he is teaching too. Eugene is dealing with machine learning since the 80s, so you can imagine he has a very strong opinion about different topics in this industry. We talked about random forests, neural nets, boosting strategies, the importance of understanding data and statistics. We couldn't skip talking about the effects of the current and upcoming crisis either. Eugene's LinkedIn: https://www.linkedin.com/in/eugene-dubossarsky-09208a1/ AlphaZetta: https://alphazetta.ai/ Reask Track cyclons: https://reask.earth/ The Prediction Machines book: https://www.predictionmachines.ai/ Hopfield network: https://en.wikipedia.org/wiki/Hopfield_network Bengio talk: https://slideslive.com/38922304/from-system-1-deep-learning-to-system-2-deep-learning Finnian Lattimore and Cheng Soon Ong Paper https://arxiv.org/pdf/1806.01488.pdf ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
We recorded an extra and special (business related) episode, our guest is Marco Lemessi, who is a Machine Learning leader at John Deere. He will share some of the business aspects and also problems of the machine learning projects they are facing at one of the biggest agricultural companies in the world. He spent 18 years at John Deere, so you can imagine that he has a very broad perspective about business cases and data science and optimization problems at John Deere. He will talk about precision agriculture, problems of labeling on large dataset, legal aspects of artificial intelligence. Contact Marco on LinkedIn: https://www.linkedin.com/in/marcolemessi/ Marco's email address: LemessiMarco@johndeere.com Website of John Deere: https://www.deere.com/ ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode our guest is Abhishek Thakur, who is the Chief Data Scientist at Boost.ai in Norway. Abhishek has become the World’s first Quadruple Grandmaster on Kaggle. So we asked him about his experiences of the 150 competitions he has taken part in. So, what are the tricks here? How can someone participate in so many competitions, rank high and have a work besides these? Although he has been so successful you will see that he is a very humble person. Find Abhishek on Linkedin: https://www.linkedin.com/in/abhi1thakur/ Kaggle: https://www.kaggle.com/ Abhishek's user on Kaggle: https://www.kaggle.com/abhishek Subscribe him on YouTube: https://www.youtube.com/AbhishekThakurAbhi Website of Boost AI: https://www.boost.ai/ ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode, our guest is Benedek Rozemberczki who is a Data Science Phd candidate at University of Edinburgh and also the owner of the github repo Karate Club where he implemented more than 30 scientific papers about Graphs and ML. Karate Club: https://github.com/benedekrozemberczki/karateclub Papers on Graph Classification: https://github.com/benedekrozemberczki/awesome-graph-classification Papers on Node (Network) Embedding: https://github.com/chihming/awesome-network-embedding Papers on Graph Neural Networks: https://github.com/naganandy/graph-based-deep-learning-literature Papers on Graph Clustering: https://github.com/benedekrozemberczki/awesome-community-detection Deep Learning on Graphs: https://pytorch-geometric.readthedocs.io/en/latest/ https://www.dgl.ai/ Graph Kernels: https://github.com/jajupmochi/graphkit-learn Datasets https://snap.stanford.edu/ https://ls11-www.cs.tu-dortmund.de/staff/morris/graphkerneldatasets https://chrsmrrs.github.io/datasets/ ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode our guest is Max Sklar who works as Engineering and Innovation Labs advisor at Foursquare. We talked about ratings and the problems about deciding if a rating is positive or negative, and the problems about different languages. In the second part of the show we talked about marketing attribution and causality. Max’s Linkedin: https://www.linkedin.com/in/max-sklar-b638464/ The Local Max Radio (podcast): https://www.localmaxradio.com/ Publication Timely Tip Selection for Foursquare Recommendations: http://ceur-ws.org/Vol-1247/recsys14_poster18.pdf Venue rating system blog post: https://medium.com/foursquare-direct/finding-the-perfect-10-how-we-developed-the-foursquare-venue-rating-system-c76b08f7b9b3 ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode, my guest is Diganta Misra, who is the founder of Landskape AI, which is a research lab aimed at solving the most challenging questions of Deep Learning. Diganta is a Mathematician who invented the activation function called MISH, which beats Google's activation function called Swish in most computer vision tasks. He released his paper last summer and the project got already 600 stars on Github. He is already working on the next activation function called SharkFIN, which will be even better than MISH. Contact Diganta on LinkedIn: https://www.linkedin.com/in/misradiganta/ Diganta's Email: mishradiganta91@gmail.com Diganta's Github: github.com/digantamisra98 Diganta's Twitter: https://twitter.com/DigantaMisra1 Landskape AI webpage: landskape.org MISH Paper: https://arxiv.org/abs/1908.08681 MISH project on Github: https://github.com/digantamisra98/Mish ---General Info--- About the host: Miklos Toth is a Machine Learning enthusiast who is also teaching Machine Learning and Deep Learning at international companies, working on various ML projects as an engineer. About the co-host: Levente Szabados is a Deep tech leader, consultant, and manager with a special interest in artificial intelligence, cognitive sciences, data science, and deep learning. He is teaching various ML courses at the Frankfurt School of Finance and Management. About the podcast: The podcast was created to serve the technical community with details of ML algorithms, use-cases. The episodes are recorded in Budapest, Hungary, Europe. Website of the podcast: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Co-Host LinkedIn: https://www.linkedin.com/in/levente-szabados-76334728/ Write an email to the host: miklos@machinelearningcafe.org Equipment: On the host's side the show is recorded with Rode Procaster and with Roland Quad-Capture audio interface. ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode, I talked with Curtis Northcutt about his application cleanlab, with which you can find label errors in your dataset. Cleanlab computes cross-validated probabilities, the confident joint, and the statistics used in uncertainty estimation for dataset labels, and it ranks and sorts the labels by the probabilities of error, so you can easily find them in your dataset. Curtis' website: https://www.curtisnorthcutt.com/ Curtis on LinkedIn: https://www.linkedin.com/in/cgnorthcutt/ Cleanlab on GitHub: https://github.com/cgnorthcutt/cleanlab Cleanlab's blog: https://l7.curtisnorthcutt.com/cleanlab-python-package White Papers: https://arxiv.org/abs/1911.00068 https://arxiv.org/abs/1705.01936 Music by Curtis (PomDP the PhD rapper): https://soundcloud.com/thephdrapper/bars-on-bars https://soundcloud.com/thephdrapper/crown https://soundcloud.com/thephdrapper/dub-dub https://open.spotify.com/album/2Fjg3zF8PGEg9WWNoeyx3X ---General Info--- Podcast's Website: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Email of the host: miklos@machinelearningcafe.org ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro: "Bars on Bars" by Curtis Northcutt (with his explicit allowance to play)
In this episode, we interview Less Wright, who has set 13 records on the fast.ai leaderboard, and we talk about one of his tricks is using cutting-edge optimizers, he also developed one, which is called Ranger. He talks also about different strategies of using Deep Learning optimizers, it is worth to take those into consideration. We also tested Ranger and in our case, it also outperformed Adam/RAdam variants. Co-host is Levente Szabados. Less' LinkedIn: https://www.linkedin.com/in/less-wright-22b59017/ Ranger's article: https://medium.com/@lessw/how-we-beat-the-fastai-leaderboard-score-by-19-77-a-cbb2338fab5c Less' medium articles: https://medium.com/@lessw His article about Mixnet he mentions: https://medium.com/@lessw/meet-mixnet-google-brains-new-state-of-the-art-mobile-ai-architecture-bd6c37abfa3a His Github: https://github.com/lessw2020 Co-Host: Levente Szabados https://www.linkedin.com/in/levente-szabados-76334728/ ---General Info--- Podcast's Website: http://machinelearningcafe.org/ Host's LinkedIn: https://www.linkedin.com/in/miklostoth/ Email of the host: miklos@machinelearningcafe.org ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode, we are focusing on Deep Learning Optimizers, the different Gradient Descent Variants from vanilla GD to RAdam and Ranger. Levente tells us the story of GD from the simplest ones to the newest ones. This is part 1. Levente's Linkedin URL: https://www.linkedin.com/in/levente-szabados-76334728/ An overview of gradient descent optimization algorithms: https://arxiv.org/pdf/1609.04747.pdf Lookahead optimizer algorithm: https://arxiv.org/pdf/1907.08610.pdf Ranger optimizer by Less Wright: https://medium.com/@lessw/new-deep-learning-optimizer-ranger-synergistic-combination-of-radam-lookahead-for-the-best-of-2dc83f79a48d ---Copyright Info--- Music is from https://filmmusic.io, intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode, we interview Renee Ahel, who is a Lead AI Expert at Cirtuo and a freelance data scientist in Croatia. He is dealing with Machine Learning since 2003, and recently he is working on Tree-based methods, with which he solves procurement problems. He is also dealing with Expert systems, you will hear why. His motto is: You should choose the most efficient tool for the problem you have, regardless of whether it is in fashion or not. AI applications in procurement: https://sievo.com/resources/ai-in-procurement Expert systems https://en.wikipedia.org/wiki/Expert_system Kraljic matrix https://www.forbes.com/sites/jwebb/2017/02/28/what-is-the-kraljic-matrix/#2d004b38675f Bayes network powered PCOS (polycystic ovary syndrome) diagnostics - implemented by Croatian company Vingd for the Berlin startup Clue: https://techcrunch.com/2019/09/04/period-app-clue-hopes-to-predict-if-you-have-pcos/ Renee Ahel on LinkedIn: https://www.linkedin.com/in/reneeahel/ Data Science Croatia: https://www.meetup.com/DataScienceCroatia/
In this Episode we talked about the deep neural networks and the spectral density of each layer's weights. It turns out, you can predict the accuracy ( and many more) with the WeigthWatcher application. We talk about the 5+1 Phases of learning and Heavy Tailed Self Regularization. Charles Martin, PhD on LinkedIn: https://www.linkedin.com/in/charlesmartin14/ During the episode we talked about these VC Theory: https://en.wikipedia.org/wiki/Vapnik%E2%80%93Chervonenkis_theory Why Deep Learning works? post by Charles Martin, 2015 https://calculatedcontent.com/2015/03/25/why-does-deep-learning-work/ Presentation at Berkeley: Why Deep Learning works? by Charles Martin, 2016 https://www.youtube.com/watch?v=fHZZgfVgC8U Several Papers written by Charles Martin and Michael Mahoney: https://arxiv.org/search/?query=%22Charles+H.+Martin%22&searchtype=author&abstracts=show&order=-announced_date_first&size=50 Newest blog post about weightwatcher, 2019 December: https://calculatedcontent.com/2019/12/03/towards-a-new-theory-of-learning-statistical-mechanics-of-deep-neural-networks/ WeightWatcher on GitHub: https://github.com/CalculatedContent/WeightWatcher easy installation for python users: pip install weightwatcher How to reach out: https://calculationconsulting.com/ charles@calculationconsulting.com To access their slack channel please contact Charles first. ---Copyright Info--- Music is from https://filmmusic.io , intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
In this episode, we talked about the idea behind GANs in general and two special types of GANs: Progressively Growing GANs and Style GANs. LinkedIn URL of Alexandr Honchar: https://www.linkedin.com/in/alexandr-honchar-4423b962/ Companies where Alex works: http://neurons-lab.com/ http://mawi.band/ Facebook: https://www.facebook.com/rachnogstyle Blog about ECG pipeline: https://medium.com/mawi-band/towards-ai-based-only-biosignal-analysis-pipeline-39e6e31244a6 Progressively Growing GANs: https://www.youtube.com/watch?v=G06dEcZ-QTg https://arxiv.org/abs/1710.10196 StyleGAN: https://arxiv.org/abs/1812.04948 https://machinelearningmastery.com/introduction-to-style-generative-adversarial-network-stylegan/ ---Copyright Info--- Music is from https://filmmusic.io , intro first part is by Miklos Toth and some free garage band loops. :) intro second part: "Aces High" by Kevin MacLeod, outro "Acid Trumpet" by Kevin MacLeod (https://incompetech.com), License: CC BY (http://creativecommons.org/licenses/by/4.0/)
