##About the 2019 edition:
The schedule for the 2019 edition is published here: https://hasgeek.com/anthillinside/2019/schedule
The conference has three tracks:
- Talks in the main conference hall track
- Poster sessions featuring novel ideas and projects in the poster session track
- Birds of Feather (BOF) sessions for practitioners who want to use the Anthill Inside forum to discuss:
- Myths and realities of labelling datasets for Deep Learning.
- Practical experience with using Knowledge Graphs for different use cases.
- Interpretability and its application in different contexts; challenges with GDPR and intepreting datasets.
- Pros and cons of using custom and open source tooling for AI/DL/ML.
#Who should attend Anthill Inside:
Anthill Inside is a platform for:
- Data scientists
- AI, DL and ML engineers
- Cloud providers
- Companies which make tooling for AI, ML and Deep Learning
- Companies working with NLP and Computer Vision who want to share their work and learnings with the community
For inquiries about tickets and sponsorships, call Anthill Inside on 7676332020 or write to sales@hasgeek.com
#Sponsors:
Sponsorship slots for Anthill Inside 2019 are open. Click here to view the sponsorship deck.
Anthill Inside 2019 sponsors:
#Bronze Sponsor
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#Community Sponsor
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Hosted by
Anthill Inside is a forum for conversations about risk mitigation and governance in Artificial Intelligence and Deep Learning. AI developers, researchers, startup founders, ethicists, and AI enthusiasts are encouraged to: more
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mira abboud
@mira_abboud
Artificial Intelligence for automated investment
Submitted Oct 14, 2019
Section:
Full talk
Technical level:
Advanced
Session type:
Lecture
Neotic.ai introduced the use of AI for assisting investors in decision making. The technology behind it is based on machine learning algorithms for price patterns recognition, corporate fundamentals, and financial news analysis. The company offers customized AI to hedge funds as well as plug and play, fully automated trading strategies.
Outline
The talk will cover the following areas:
- AI in finance vs AI in other fields.
- Challenges faced while applying machine learning algorithms on stock market data (Daily data, problems of Over/Under fitting, fat tails, etc).
- Limitations/problems of Supervised and Unsupervised learning
- State of the art solutions.
Requirements
None
Speaker bio
As a CTO and a data scientist at Neotic.ai SAL, Dr. Mira Abboud leads Neotic’s long-term technology vision from supervising the technical team to improving the data science process development and is responsible for implementing new ideas after studying their feasibility. Mira is a Computer Sciences instructor at Lebanese University and researcher in the AI field. Holder of a Ph.D focused on AI and software architectures extraction, from local & Nantes (France) university. Her Publications include “Towards Using KDD for an Interactive Software Architecture Extraction” and “KDD extension tool for software architecture extraction”.
Comments
Hosted by
Anthill Inside is a forum for conversations about risk mitigation and governance in Artificial Intelligence and Deep Learning. AI developers, researchers, startup founders, ethicists, and AI enthusiasts are encouraged to: more
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