See the Top Rated Talks from ODSC APAC 2020 Here
ConferencesModelingAPAC 2020APAC 2021posted by ODSC Team June 25, 2021 ODSC Team
We are deep into planning mode for ODSC APAC Virtual 2021, coming to your computer September 15th-16th. We aren’t quite ready to announce talk titles just yet, but we can promise you they will be as relevant and thought-provoking as those from ODSC APAC 2020. To give you an idea of what to expect, check out a few of ODSC APAC 2020’s talks below.
Privacy-Preserving Machine Learning Techniques: Amogh Kamat Tarcar | Team Lead (CTO ML Team) | Persistent Systems Ltd.
Federated Learning with its decentralized strategy for building machine learning models, is a good option for situations where aggregating data in a central location, especially when it is paired with privacy-preserving techniques such as encryption and differential privacy.
This ODSC APAC talk will bring you up to speed with the progress on privacy-preserving machine learning while discussing platforms for developing models and present a demo on healthcare use cases.
AI Singapore’s Journey into the World of Federated Learning: Jianshu Weng, PhD | Head of Federated Learning Lab | AI Singapore
AI Singapore has been working on building a system, named Learn, about the key components of Synergos, AI Singapore’s system for supporting Federated Learning, a key tool for preserving privacy by training models across multiple decentralized parties holding local data, without exchanging them.
Data Science and Machine Learning at Scale: Hugo Bowne-Anderson, PhD | Head of Data Science Evangelism | Coiled
Learn everything you wanted to know about scaling your data science work to larger datasets and larger models, while staying in the comfort of the PyData ecosystem (NumPy, pandas, scikit-learn, Jupyter notebooks).
Normalizing User-Generated Text Data: Piyush Makhija | Machine Learning Engineer | Vahan, Inc
In this ODSC APAC talk, you will learn about Vahan, Inc’s approach, experience, and learnings from designing a robust system to clean noise in data, without handcrafting the rules, using Machine Translation, and effectively making downstream NLP tasks easier to perform. They were motivated to create this system by their experience building a conversational system over WhatsApp to screen candidates for blue-collar jobs.
Text Extraction from Images Using Deep Learning Techniques: Rajesh Shreedhar Bhat | Data Scientist | Walmart Labs, Pranay Dugar | Data Scientist | Walmart Labs
Extracting texts of various sizes, shapes, and orientations from images containing multiple objects is an important problem in many contexts, especially, in connection to e-commerce, augmented reality assistance system in a natural scene, content moderation in social media platforms, etc.
In this session, you’ll learn about the character-level text detection for detecting normal and arbitrary shaped texts, the CRNN-CTC network, and the need for CTC loss to obtain the raw text from the images.
Register now for ODSC APAC 2021
ODSC APAC 2021 is sure to feature even more insightful and engaging talks on the latest advancements in data science and AI. So, be sure to reserve your pass here for 75% off!