-
8th Meetup: EDA with Plotly & Predicting Patients No Show
Hello Everyone, Ramadan Mubarak! In this meetup we had two amazing speakers: 1st lightning talk : Dr. Dhaifallah Alwadani In this lightning talk, Dhaifallah will show how he used xgboost to predict no-shows and automate intervention. 2nd Tutorial: Ahmed Karam In this tutorial he will introduce you to the Plotl... Read More
-
The Sovereign Machine Learner
In this talk Mark shares his perspective on the current state of ML engineering careers and discusses the unschooled model to educating yourself about ML, science, and engineering. Resources Slide Deck How I read Technical books I love Reflections on one school worldhouse How to get a great job Deschooling society The s... Read More
-
Graph Algorithms and Neo4j Introduction
In this talk Mark Needham explains graph algorithms that provide one of the most potent approaches to analysing connected data. They describe steps to be taken to process a graph to discover its general or specific quantities. In this talk we will introduce you to the Neo4j Graph Algorithms library, giving a brief overview of the differe... Read More
-
Improving Non-English Tools for Digital Assistants
In this talk we have had Vincent . He showed us how Rasa works. With creating a simple chatbot from the command line and give an overview of how the NLU pipelines work. He also explained his new effort to make this technology more available for non-English users. He demonstrated some tools he’s made available for Arabic but he’d ... Read More
-
MLflow: An open platform for the machine learning lifecycle - part 2
As per your demands we have Abdulrahman Alfozan back with us for MLflow part 2. In this talk Abdulrahman has explored MLflow's components intended for model serving in production: a) MLflow projects for reproducibility and sharing. b) MLflow models for deployment-ready abstractions. Slides : Project repo and documentation Read More
-
Building a Visual Interface for your ML Model with Gradio
Accessibility is a major challenge of machine learning (ML). Typical ML models are built by specialists and require specialized hardware/software as well as ML experience to validate. The accessibility challenge also makes collaboration more difficult and limits the ML researcher’s exposure to realistic data and scenarios that occur in the wi... Read More
-
MLflow: An open platform for the machine learning lifecycle
Everyone who has tried to do ML development knows that it is complex. Beyond the usual concerns in the software development, ML development comes with new challenges: There are a myriad tools It’s hard to track experiments It’s hard to reproduce results It’s hard to deploy ML And because of these challenges, it is clear that ML developm... Read More
-
ARBML: Democratizing Arabic NLP
This talk has been Presented by Zaid Alyafeai. He talk about ARBML, an open source project that makes NLP models more accessible through several interfaces ARBML goal is to enrich the Arabic content by creating open-source projects and open the community eyes on the significance of machine learning. ARBML procedure is generalized and can be ... Read More