BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//cfp.devcon.org//devcon8//speaker//DA9M99 BEGIN:VTIMEZONE TZID:IST BEGIN:STANDARD DTSTART:20000101T000000 RRULE:FREQ=YEARLY;BYMONTH=1 TZNAME:IST TZOFFSETFROM:+0530 TZOFFSETTO:+0530 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:pretalx-devcon8-ZWHMKX@cfp.devcon.org DTSTART;TZID=IST:20261105T140000 DTEND;TZID=IST:20261105T141500 DESCRIPTION:Training an AI model can take minutes\, hours or days. Waiting until the end to inspect a log file is often too late: loss may already be diverging\, gradients may be behaving unexpectedly\, validation performan ce may have stopped improving\, or a data pipeline may simply be producing the wrong results.\n\nVisdom provides an open-source way to see what is h appening while an experiment is running.\n\nIn this session\, Norbert Prei ning will show how Python applications and machine-learning workflows can send live data to Visdom and turn a running experiment into an interactive dashboard. Starting with only a few lines of Python\, we will look at str eaming loss and accuracy curves\, NumPy data\, images and model outputs di rectly into the browser.\n\nThe session will then move from individual plo ts to complete ML workflows: monitoring PyTorch and PyTorch Lightning trai ning\, collecting TensorFlow/Keras metrics\, organizing experiments\, reco rding hyperparameters and comparing runs. We will also look at how Visdom can be used to inspect images\, embeddings and other intermediate results while a model is still training.\n\nA key idea behind Visdom is that visua lization should remain separate from the computation itself. Your training framework computes the metrics\; Visdom receives\, stores and visualizes them. This keeps the integration small\, makes Visdom usable with many dif ferent frameworks and allows developers to run the visualization server lo cally\, on their own infrastructure or alongside remote training systems.\ n\nThe latest Visdom work also makes this approach useful for larger exper iment workflows: experiments can carry parameters\, metrics and tags\, run s can be searched and compared\, and live results can be explored through hyperparameter and experiment views.\n\nThe talk will use short code examp les and live visualizations to show how quickly a normal Python or ML trai ning loop can become observable.\n\nWhether you are training a PyTorch mod el\, working with TensorFlow/Keras\, exploring NumPy data or building your own AI pipeline\, the goal is the same:\n\n**don't wait for the experimen t to finish to understand what it is doing.** DTSTAMP:20261101T042014Z LOCATION:Community Led Stage SUMMARY:Watch Your Models Learn: Real-Time AI/ML Experiments with Visdom - Norbert Preining URL:https://cfp.devcon.org/devcon8/talk/ZWHMKX/ END:VEVENT BEGIN:VEVENT UID:pretalx-devcon8-DUU3MK@cfp.devcon.org DTSTART;TZID=IST:20261105T161500 DTEND;TZID=IST:20261105T170000 DESCRIPTION:Every 12 seconds\, Ethereum produces a new block full of transa ctions\, fees and smart-contract activity. Most people only see this data as a list of hashes on a block explorer. In this hands-on workshop\, you w ill turn it into a live dashboard of your own.\n\nWe'll use Visdom and [We b3.py](http://Web3.py) to connect to an Ethereum node and stream blockchai n data into charts. By the end of the session\, each participant will have a working dashboard that updates with every new block\, showing:\n\n- bas e fee and priority fee over time\n\n- transactions per block\n\n- legacy v s. EIP-1559 transaction types\n\n- the distribution of ETH transferred\n\n - a network overview panel with the latest headline figures\n\nYou'll lear n how to arrange and save dashboard layouts\, and how to set up separate e nvironments for mainnet\, testnets or individual contracts. We'll also loo k at next steps: smart-contract analytics\, DeFi and NFT tracking\, node h ealth monitoring\, and visualizing machine-learning models trained on on-c hain data\, such as anomaly or bot detection.\n\nNo blockchain experience is needed. Basic Python is enough.\n\n**What participants bring:** A lapto p with Python 3 installed\, and a free Ethereum RPC endpoint from any prov ider. It would help to share setup instructions in advance so no workshop time goes to installs. DTSTAMP:20261101T042014Z LOCATION:CLS - Builders Room SUMMARY:How to use Visdom to Visualize Ethereum and Blockchain Data - Manik Khajuria\, Norbert Preining\, Jayant Parashar\, Rajnish Tiwari\, Vedansh Saini URL:https://cfp.devcon.org/devcon8/talk/DUU3MK/ END:VEVENT BEGIN:VEVENT UID:pretalx-devcon8-LAFSE7@cfp.devcon.org DTSTART;TZID=IST:20261105T170500 DTEND;TZID=IST:20261105T173500 DESCRIPTION:Bring your questions to the people who build and maintain FOSSA SIA's open source projects. In this open session\, FOSSASIA maintainers an d GSoC mentors answer anything from the audience: how to make your first c ontribution\, what maintainers look for in a pull request\, how projects l ike Eventyay\, Voxbento\, Visdom\, PSLab\, Badge Magic are run day to day\ , and how you can get involved in FOSSASIA CodeHeat\, Google Summer of Cod e and other programs. DTSTAMP:20261101T042014Z LOCATION:Community Led Stage SUMMARY:What FOSSASIA Maintainers Wish Contributors Knew: Ask Us Anything - Srivatsav Auswin\, Arnav Angarkar\, Norbert Preining\, Saksham Sirohi URL:https://cfp.devcon.org/devcon8/talk/LAFSE7/ END:VEVENT END:VCALENDAR