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Activities & events
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Knowledge Graphs and LLMs Across Academia and Industry - Anahita Pakiman
2024-04-05 · 16:00
Anahita Pakiman
– guest
We talked about: Anahita's Background Mechanical Engineering and Applied Mechanics Finite Element Analysis vs. Machine Learning Optimization and Semantic Reporting Application of Knowledge Graphs in Research Graphs vs Tabular Data Computational graphs Graph Data Science and Graph Machine Learning Combining Knowledge Graphs and Large Language Models (LLMs) Practical Applications and Projects Challenges and Learnings Anahita’s Recommendations Links: GitHub repo: https://github.com/antahiap/ADPT-LRN-PHYS/tree/main Free Data Engineering course: https://github.com/DataTalksClub/data-engineering-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html |
DataTalks.Club |
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Knowledge Graphs and LLMs Across Academia and Industry
2024-03-20 · 11:30
Graph retrieval systems and building a Python package - Anahita Pakiman About the event Outline:
About the speaker Anahita is a Data scientist-engineer with a strong background in the knowledge graph, semantic web, digitalization, and mechanical engineering. Currently the Senior Knowledge Graph-Data Scientist Consultant at brox IT-Solutions DataTalks.Club is the place to talk about data. Join our slack community! |
Knowledge Graphs and LLMs Across Academia and Industry
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Teach papers to 5 years old
2023-09-19 · 15:30
Wanna be able to read a paper from a domain you know nothing about ? Use our tool to get explanations of every term used in the paper. A concept is used in the explanation that you don’t know ? Go deeper again until you reach the explanation of for example addition or any simple concept that a 5 years old could understand, if he knows how to read of course ! Built using ChatGPT and other sources. |
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Value Investing Hypothesis testing
2023-09-19 · 15:30
Testing Benjamin Graham's value investing system in stock market using selected value investing features of data input from the quarterly financials of companies. Value investing is interested in the real calculated value of each company according to its financials and has no interest in the price fluctuations of the market. Hence a portfolio of stocks are selected that are cheap and long term return are collected until the stock price reachs saturation. Project is going to feed in these features (collected from historical stock data) into a model and hope to come up with a better weighted system with the help of data science and machine learning practices. |
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CodeWhiz- the specialized coding assistant
2023-09-19 · 15:30
We are embarking on the creation of a specialized programming assistant, meticulously fine-tuned for libraries such as PyTorch, TensorFlow, or Dart, FastAIs. This intelligent assistant, accessible through a chat-like interface, is designed to offer tailored guidance, provide access to the latest documentation, and suggest learning resources to users. It will comprehend contextual queries, ensuring deep library expertise, and offer direct links to official documentation, facilitating efficient problem-solving and learning. With continuous updates, personalization options, and a commitment to privacy, this coding assistant aims to significantly enhance the development experience for programmers and serve as an invaluable resource in the ever-evolving landscape of software development. |
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AI based Wind Power Predictions
2023-09-19 · 15:30
In recent years, and with increasing installation of renewable energy, the demand for accurate wind power prediction is growing, in order to keep grid stability at a high level, This project aims to use rather large scale numerical weather predictions and map it to local measurements. In a next step local weather predictions are combined with historical operational data of a large wind farm and the production in the next 48h is forecasted. |
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Social media Stats Servant (Social media debugging)
2023-09-19 · 15:30
The idea is to evaluate a text (e.g., a Tweet) and to provide references pointing to an official source (e.g., official statistics from the German federal government). Since automatic fact checking proves to be hard and a slippery affair, the stats servant is supposed to make it easy for humans to spot and counter disinformation. By delivering official statistics in reference to allegations made on social media, we build a little helper to sober debate on the internet. Starting small with statistics for a narrowly defined subject area it would be nice to branch out to areas populists usually exploit. |
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