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welcome to the Egging Phase course
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this course
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has been designed to teach you all about the
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egging phasical system
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to use the data set on Model Hub
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as well as all open source libraries
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here is the table of contents
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as you can see
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is divided in three sections
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which become progressively more advanced
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at this stage
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the first two sections have been released
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so first we'll teach you
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the basics of how to use the transformer model
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find your need on your own dataset
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and share the result with the community
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so second
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we'll dive deeper into our libraries and teach you
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how to tackle any NLP task
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we are actively working on the last one
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a note to have been
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treated for you for the spring of 2022
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the first chapter requires no technical knowledge
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and is a good introduction to learn what transformers
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model can do
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and all we could be reviews to you are your company
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the next chapters recall your good knowledge of Titan
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and some basic knowledge of machine learning
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and deep learning
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if you don't know what the training and validation set
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are or what gradient decent means
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you should look at an introductory course
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such as the ones published by Deep Learning the Tai
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or Faster Tai
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it's also best if you have some basics in one
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deploning framework
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by touch or turns a flow
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each part of the material introduced in this course
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as a version in both verse frameworks
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so we'll be
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able to pick the one you are most comfortable with
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this is the team that developed this course
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I'll now let
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each of the speakers introduce themselves briefly
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hi my name is Matthew
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and I'm a machine learning engineer at huggingface
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I work on the open source team
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and I'm responsible for maintaining
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particularly the Tensorflow code there
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previously I was a machine learning engineer at parsley
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who have recently been acquired by Automatic
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and I was a postdoctoral researcher before that at
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Trinity College Dublin in Ireland
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working on computational genetics and retinal disease
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hi I'm Lysander
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I'm a machinery
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engineer at Hugging Face and I'm specifically part
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of the open source team
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I've been a hugging face for a few years now
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and alongside my team members
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I've been
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working on most of the tools that you'll get to see in
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this course
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hi I'm Silva
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I'm a research engineer at tuggingface
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and one of the main maintainers
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of the Transformers library
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previously I worked at Faster AI
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where I helped develop the Faster AI library
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as well as an online book
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before that
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I was a math and computer science teacher in France
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hi
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my name is Sasha and I'm a researcher at huggingface
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working on the ethical
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environmental
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and social impacts of machine learning models
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previously I was a postdoctoral researcher
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at Milan University of Montreal
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and I also worked as an applied AI
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researcher for the United Nations
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Global Pulse
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I've been involved in projects such as Code Carbon
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and the Machine Learning Impacts Calculator
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to measure the carbon footprint of machine learning
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hi I'm Mervy and I'm a developeradvicat Huggingphase
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previously I was working as a machine learning engineer
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building NLP tools and chatbots
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currently I'm working to improve the hub
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and democratize machine learning
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hello everyone
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my name is Lucille
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and I'm a machine learning engineer at erginface
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to tell you in two sentences who I am
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I work on the development on support
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of open source tools
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and I also participate in several research projects
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in the field of
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natural language posting
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good day there
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I'm Lewis
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and I'm a machine learning engineer in the open
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source team at huggingface
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I'm passionate about developing tools
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for the NLP community
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and you'll see me at many of Huggingface's outreach
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activities
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before joining huggingface
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I spent several years
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developing machine learning applications
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for startups and enterprises in the domains of NLP
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topological data analysis and time series
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in a former life I was a theoretical physicist
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where I research particle collisions at the Large
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Hadron Collider and son
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hey I'm Leandro
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and I'm a machine learning engineer in the
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open service team at huggingface
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before joining huggingface
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I worked as a data scientist in Switzerland
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and have taught data science at university
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