A Deep Dive into Continuous Thought Machines
Explore the Continuous Thought Machine (CTM), a neural network architecture that integrates neuron-level timing and
ADaSci Expert
Олександр Денисюк
Mastering AI Code Execution in Secure Sandboxes with E2B
Explore how E2B provides secure, isolated sandboxes for running AI-generated code with LLaMA-3 on Together
How L&D Leaders Can Drive AI Readiness Across the Enterprise?
A strategic guide to AI Readiness helping L&D leaders align talent, tools, and training for
Chartered Data Scientist (CDS™)
The highest distinction in the data science profession. Not just earn a charter, but use it as a designation.
Upcoming Workshop on Generative AI to Solve Complex Business Problems
In this workshop we are going deeper into Generative AI and presenting how to utilize
Take the Generative AI Crash Course: A Virtual Hands-on Workshop by ADaSci
ADaSci is organizing this virtual hands-on workshop on 4th March 2023.
Deep Learning DevCon 2023: Virtual Conference by ADaSci on May 27
ADaSci organizes the DLDC 2023, the third edition of annual conference Deep Learning DevCon, to
ADaSci launches its chapters to boost the worldwide data science ecosystem
ADaSci plans to make the community more active and accessible to its members through chapters.
Why should you become a member of ADaSci?
Professional bodies provide better networking opportunities to connect with others working in the field of
How does Institutional membership with ADaSci add value to a brand?
Any corporate, organization or academic institution having common interests in data science or relevant fields
Application of Ensemble Clustering to Create Consumption Behavior based Store Clusters
Author(s): Varen Gupta
Exploration of Linear Model fit using observation weights and parameter constraints to handle poor quality data
Author(s): Ullas M S Rao, Mattias Jönsson
IntelliQSense: An intelligent, real-time Query Autocompletion Framework using GPT-2
Author(s): Taaniya Arora, Shashank Srivastava, Neha Prabhugaonkar
EthicalFL – An Optimized Federated Learning Framework with Bias Mitigation
Author(s): Shekar Ramachandran, Aakshi Mittal, Rudra Nath Palit, Anmol Bhasin, Aruna Kumari V, Rupali Agrahari,
