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Austin Python Meetup
United States
Приєднався 11 січ 2021
The home of Austin Python Meetup.
www.meetup.com/austinpython/
www.meetup.com/austinpython/
Hamza Farouk - Retrieval’s retrieval in RAG Systems
Talk: Hamza Farouk - Retrieval’s retrieval in RAG Systems.
Abstract: This project attempts to use an unusual approach for information retrieval in a RAG system. It first attempts to retrieve the most similar sentence in the document and uses the retrieved sentence to retrieve a larger chunk of the document that has more context for the RAG.
Bio: I am an AI enthusiast looking for career opportunities in the field. I have a background in engineering and I have previously worked in various industries from electronics to manufacturing to digital marketing.
Abstract: This project attempts to use an unusual approach for information retrieval in a RAG system. It first attempts to retrieve the most similar sentence in the document and uses the retrieved sentence to retrieve a larger chunk of the document that has more context for the RAG.
Bio: I am an AI enthusiast looking for career opportunities in the field. I have a background in engineering and I have previously worked in various industries from electronics to manufacturing to digital marketing.
Переглядів: 74
Відео
Jackson Henry: AI/ML in Action: Simplilearn Capstone Project: Healthcare
Переглядів 1502 місяці тому
Talk : Jackson Henry: AI/ML in Action: Simplilearn Capstone Project: Healthcare Abstract: Simplilearn is one of the world’s leading global digital skills providers which helps empower learners worldwide to achieve their career goals. Founded in 2010, Simplilearn offers a wide variety of bootcamps, online courses, and certifications. This project is the capstone project for the Artificial Intell...
Thomas Mock - Super-powered notebooks with Python and Quarto
Переглядів 1152 місяці тому
Talk: Thomas Mock - Super-powered notebooks with Python and Quarto Description: Quarto is an open-source scientific and technical publishing system that builds on standard markdown with features essential for scientific communication. The system supports reproducible embedded computations, equations, citations, crossrefs, figure panels, callouts, advanced layouts, WASM, and more for PDF/HTML re...
Mason Egger - Build Durable Applications with Temporal
Переглядів 905 місяців тому
Mason Egger - Build Durable Applications with Temporal Description: Applications crash. This is an unfortunate reality of software development. Hard drives fail, networks go down, external APIs stop responding, the list goes on and on. Much of a developer's time is spent writing code to handle such errors. But what if that wasn't the case? What if you could deploy applications that could surviv...
Jacob Barhak - ClinicalUnitMapping.Com Takes a Small Step Towards Machine Comprehension of Clinical
Переглядів 667 місяців тому
Jacob Barhak - ClinicalUnitMapping.Com Takes a Small Step Towards Machine Comprehension of Clinical Trial Data Session: Clinical Trial data is not standardized and numerical data cannot be comprehended since the units are not standardized. ClinicalUnitMapping.com is a web tool constructed to help standardize this data and merge it with the following standards and specifications: UCUM, RTMMS / I...
Pete Zaitcev - Python in OpenStack Swift
Переглядів 847 місяців тому
Pete Zaitcev - Python in OpenStack Swift Summary: OpenStack Swift is a project that delivers an object server, with an interface broadly similar to Amazon S3. Swift is written in Python, and is used by a number of organizations such as cellphone companies, governments, and technology companies. Because Swift moves data by itself, or is a "data plane" service, its implementation focuses on perfo...
Drake How to make a BOSS robust website using django, fast.No fluff included
Переглядів 668 місяців тому
How to make a BOSS robust website using django, fast.No fluff included Description: In this talk, I will cover the following topics: Cookie cutter setup Cookie cutter settings Django API Django public view HTML Prerequisites: windows docker desktop github python miniconda Bio: I have a Bachelor of Science in Computer Science and am Security Certified. I love automation and my favorite AI are Ja...
Jay Miller: Python Web Testing Near and Far with Playwright
Переглядів 638 місяців тому
Jay Miller- Python Web Testing Near and Far with Playwright Description: Testing a web application is often beyond testing the code that builds it. Many times your local deployments and your production deployments will differ in some small way. Instead of writing multiple tests we can test from a different angle. Enter Playwright, a modern frontend testing framework. In this presentation we'll ...
Chris Leonard HTMX: HTTP interactions implemented directly in HTML
Переглядів 799 місяців тому
HTMX: HTTP interactions implemented directly in HTML HTMX is a project that facilitates interactive web applications without the need for extensive custom JavaScript code. In this talk, we will learn how Python developers can use HTMX to build full-stack apps while focusing on the backend layer. Chris Leonard is an Austin, Texas-based software engineer with nearly 25 years of experience, contin...
Peter Vidos - Creating Interactive, Animated Reports in Streamlit with Vizzu
Переглядів 2989 місяців тому
Talk: Peter Vidos - Empowering Data Exploration: Creating Interactive, Animated Reports in Streamlit with Vizzu Description: Data scientists strive to bridge the gap between raw data and actionable insights. Yet, the actual value of data lies in its accessibility to non-data experts who can unlock its potential independently. Streamlit (streamlit.io/), celebrated for its user-friendly data app ...
Sophia Yang: AI explainability
Переглядів 172Рік тому
Talk slides: sophiamyang.github.io/slides-XAI/ Description: There has been an increasing interest in AI and ML interpretability and explainability. Researchers have designed many explanation techniques such as SHAP, LIME, explainable boosting machine, visual analytics, distillation, prototypes, saliency map, counterfactual, feature visualization, interpretML, and TCAV. In this talk, we will pro...
Amirreza Salamat: Using Apache Airflow for task scheduling
Переглядів 182Рік тому
Description: Apache Airflow is a powerful tool for automating task scheduling in data processing and Machine Learning pipelines. With Airflow, developers can define workflows as code, making it easy to manage and maintain complex workflows that may involve multiple dependencies and conditions. Airflow's rich library of operators and providers makes it easy to integrate with a wide variety of se...
James Bednar - SOSA: The Scalable Open-Source Analysis Stack
Переглядів 194Рік тому
Description: Are you a researcher, scientist, engineer, data analyst, or in some other technical role where you find yourself limited by your domain’s software stack? Many technical disciplines are built around their own legacy sets of tools for storing, reading, processing, plotting, analyzing, modeling, and exploring data. Typical tools in wide use are tied to outdated architectures and assum...
Eitan Netzer - DataHeroes Python Library for Building Better ML Models, 10x Faster
Переглядів 128Рік тому
Abstract: Big data requires significant time and resources to evaluate, label, clean and train to achieve a high quality model. Use the DataHeroes framework to reduce your dataset to a small subset that maintains the statistical properties and corner cases of your full dataset, then use standard libraries to explore, clean, label, train and tune your models on a smaller subset, and build a high...
Graham Waters - Augmenting Your Workflow with AI Assistants: From GitHub Copilot to chatGPT
Переглядів 185Рік тому
Talk Description: Are you a programmer looking to streamline your workflow and get more done in less time? AI assistants like GitHub Copilot and chatGPT can help you do just that. This talk will explore how these tools can help you write code faster, generate code snippets, and automate tasks. We'll also discuss the ethical considerations of using AI assistants and how to balance the benefits a...
Dor Livne - DeepVBA: A GCN approach for malicious code detection
Переглядів 147Рік тому
Dor Livne - DeepVBA: A GCN approach for malicious code detection
Johnathan Baldera: Building APIs Everyone Loves with FastAPI
Переглядів 93Рік тому
Johnathan Baldera: Building APIs Everyone Loves with FastAPI
Mason Egger - I Can't Believe It's Not Real Data! An Introduction into Synthetic Data
Переглядів 69Рік тому
Mason Egger - I Can't Believe It's Not Real Data! An Introduction into Synthetic Data
Dima Kniazev - Using Redis as Online Feature Store for Real-time Inference
Переглядів 412Рік тому
Dima Kniazev - Using Redis as Online Feature Store for Real-time Inference
Nick Schenone - Building an AI App in Under 20 Minutes Using OS MLOps tool MLRun
Переглядів 529Рік тому
Nick Schenone - Building an AI App in Under 20 Minutes Using OS MLOps tool MLRun
Val Huber: API Logic Server Creates Customizable, Executable Database Projects
Переглядів 211Рік тому
Val Huber: API Logic Server Creates Customizable, Executable Database Projects
Jason Gauci: Machine Learning Infrastructure @ Argo
Переглядів 176Рік тому
Jason Gauci: Machine Learning Infrastructure @ Argo
Christopher Leonard: Starlette Admin - Administrative Interfaces for FastAPI
Переглядів 4,1 тис.Рік тому
Christopher Leonard: Starlette Admin - Administrative Interfaces for FastAPI
Libratizing; Templatizing: Reusable Workflows with Arganteal ADepT
Переглядів 91Рік тому
Libratizing; Templatizing: Reusable Workflows with Arganteal ADepT
Uri Itai: Goodness of fit metrics for Multi-class Predictor
Переглядів 1262 роки тому
Uri Itai: Goodness of fit metrics for Multi-class Predictor
Bianca Henderson: Demystifying Custom Ansible Modules
Переглядів 3102 роки тому
Bianca Henderson: Demystifying Custom Ansible Modules
Cheng Lee: Scaling conda for a growing ecosystem
Переглядів 1292 роки тому
Cheng Lee: Scaling conda for a growing ecosystem
Is posible that a document .ipynb convert to quarto html saving the outputs from the chunks without having the data ?
Source code?
Good work. But could have explained it better - what and how does it matter per biology instead of just showing the journey of data transformation. I think this is exactly where domain knowledge comes in handy. I'm assuming you must be a cs grad. Anyways, kudos for the work and interest in biology. (I'm a biology grad with masters in pharmacology, corssing the same path of learning ML)
Very well explained. Thank you
I needed an overview to understand how it all comes together. Excellent video, thank you!!!
You do not have to tell me twice for me to switch to this shell.
I mean creating environment for player seem like a task for game coding engineer
🙃 "promosm"
I had not heard of this before today, but now I have it installed. Lol time to tinker
what a waste of a tutorial, talk about algorithms dude
What do I do when there is one bip file and multiple texture png files? (texture_01.png, texture_02.png, texture_03.png...)
Great Video. I have been very interested in Anvil due to its simplicity and speed to build. I think it a great project. I have been skeptical of using it because of its limits (perceived or actual). In particular, the front end design ability and a connection to an external cloud database. The documentation and videos seem to come mainly from anvil so they tend to show the simplicity rather than the pitfalls. To limit my risk, I want to create a independent cloud database connected to a user interface and use anvil for the admin control panel. This is a real help.
Hey Sean, I am a newbie with Anvil, using it for less than 2 weeks. It's a fantastic tool, very stable and well thinked. It can connect to external sources but the true power and simplicity of use is achieved using internal database. I am a heavy user of SQL Server and tended to use it primarily, but the ease of use of internal DB is awesome. It has everything we could want, including atomic transactions and a wide possibility of queries. About design limitations in front end, there are none. I am not a front end dev, but you can customize your HTML and JS if you want. I think Anvil is way underrated and have less users than it deserves, but the current is very mature so far as I can tell.
Hello, I'm a industrial designer and I was thinking about how to render automatically with keyshot and python scripts, can you leave Michael Verhulst's youtube or e-mail?
And does the algorithm work when I code more agents in there, is there anything I should keep in mind? Thank you.
#askAustin
classroom code is not working
Great talk, thank you!
at 7:17 top right guy made the face we all made when we saw what the presenter did
I've been playing around with xonsh for past 3 - 4 days and I actually love it. It's weird and ambiguous and very flexible. There are some bash things that it can't do, and other things that it doesn't do well, or does in an unpredictable fashion. But I think that's really cool! You can use your imagination coming up with new things to do with it. Right off the bat, I would say it's great for playing around with simple web scraping. I love to play with Beautiful Soup, and there's a lot of trial and error involved with it. With xonsh, I can try working with different objects and see what works. When I go back through the command history, it remembers entire loops of code, and I can actually edit the code loops and rerun them in the terminal until I figure out what will work. Amazing! It certainly doesn't take the place of Bash, but it is really fun to use. Thank you!
Very nice! thank you :)
Very helpful, but she sounds a bit "douchy"
I love and hate this at the same time.
『p』『r』『o』『m』『o』『s』『m』
Hi does pyscript can be use to do web development?
xonsh is my primary shell since a month or so ago, absolutely love it
Amazing I did it You made my day Thank you!!
Pᵣₒmₒˢᵐ 😋
coooool stuff
At minute 38, that wasn't the trained policy that was running. It was a different one. But I should look deeper at it since it's the one that seemed to lead to the second robot gaining consciousness and leaving the game.
Came here for KeyShot and subscribed when i saw the analog gear.
Thanks for sharing, Please, Can I ask you a question may be stupid, so feel free to answer or not. I was studying the theoretical side of Gmapping/particle filters SLAM approaches. In other hand, it is easy for me to launch the Gmapping Exactly like the video. Because I am M.Sc. student I am thinking about modifying the Gmapping somewhat to improve it for my own limitations. How can I access the main algorithm code ? And modify it ? Thanks in advance.
Great video! Can the Python scripts used in the video be shared?
Thanks for sharing this. It was actually very interesting and I’m definitely going to try xonsh now :)
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Thank you! Was there also a QHub talk at this meetup?