Unifying all Machine Learning Frameworks - Link to a free online lecture by the author in comments

This page summarizes the projects mentioned and recommended in the original post on /r/deeplearning

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  • robot

    Functions and classes for gradient-based robot motion planning, written in Ivy. (by Transpile-AI)

  • In this talk, we will show how unifying all Machine Learning (ML) frameworks could save everybody a HUGE amount of time and energy. Through interactive coding sessions and live demos, we will explain how Ivy (checkout lets-unify.ai) is solving this unification problem. We will focus on demos using Ivy’s 3D vision and robotics libraries, solving 3D robotic navigation and perception tasks in a 3D simulator, all in real-time. Checkout https://github.com/ivy-dl/robot for examples! Finally, we will explore how you can join and contribute to the growing Ivy community, and help us in our mission to truly unify all ML frameworks once and for all.

  • InfluxDB

    Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

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