Machine Learning Experts - Lewis Tunstall
๐ If you're interested in learning how ML Experts, like Lewis, can help accelerate your ML roadmap visit: https://bit.ly/3DDt3lD to learn more.
Lewis is a Machine Learning Engineer at Hugging Face where he works on applying Transformers to automate business processes and solve MLOps challenges. Lewis has built ML applications for startups and enterprises in the domains of NLP, topological data analysis, and time series.
In this video you'll hear Lewis talk about:
- His work on Transformers
- Deploying models into the real world
- ONNX serialization
- Large scale model evaluation
- Benchmarks
๐ค Timestamps
0:00 Intro
2:38 Lewis Tunstallโs Background
3:37 Natural Language Processing with Transformers
6:21 Deploying models into production
7:24 Transformers & ONNX format
8:29 OpenAI GPT-2 / Auto-generated text
10:51 Hugging Face Course
12:37 Machine Learning Applications
16:33 Large Scale Model Evaluation
17:49 Machine Learning Benchmarks
20:14 Common Machine Learning Mistakes
22:54 What would you do differently at the start of your career?
25:21 Best advice for someone looking to get into AI/ML?
26:22 Will AI take over the world?
27:42 When will robots be in homes everywhere?
29:18 DeepMind Podcast
31:08 Favorite Machine Learning Papers
33:56 What is the meaning of life?
35:47 Checkout Lewisโs Natural Language Processing with Transformers book
39:55 Where you can follow Lewis online
๐ Honorable mentions + links:
Leandro von Werra: https://twitter.com/lvwerra
Thomas Wolf: https://twitter.com/Thom_Wolf
NLP with Transformers: https://transformersbook.com/
Luca Perrozi: https://www.linkedin.com/in/luca-perrozzi/
ONNX Format: https://onnx.ai/
Sylvian Gugger: https://twitter.com/GuggerSylvain
Lysandre Debut: https://twitter.com/LysandreJik
DeepMind Alpha Fold: https://www.deepmind.com/research/highlighted-research/alphafold
Hugging Face Hub: https://huggingface.co/models
Hugging Face Forum: https://discuss.huggingface.co
Hugging Face Discord: https://discuss.hugging
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The Future of Natural Language Processing
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Trends in Model Size & Computational Efficiency in NLP
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Increasing Data Usage in Natural Language Processing
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In Domain & Out of Domain Generalization in the Future of NLP
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The Limits of NLU & the Rise of NLG in the Future of NLP
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The Lack of Robustness in the Future of NLP
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Inductive Bias, Common Sense, Continual Learning in The Future of NLP
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Train a Hugging Face Transformers Model with Amazon SageMaker
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What is Transfer Learning?
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The pipeline function
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Navigating the Model Hub
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Transformer models: Decoders
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The Transformer architecture
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Transformer models: Encoder-Decoders
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Transformer models: Encoders
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Keras introduction
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The push to hub API
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Fine-tuning with TensorFlow
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Learning rate scheduling with TensorFlow
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TensorFlow Predictions and metrics
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Welcome to the Hugging Face course
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The tokenization pipeline
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Supercharge your PyTorch training loop with Accelerate
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The Trainer API
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Batching inputs together (PyTorch)
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Batching inputs together (TensorFlow)
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Hugging Face Datasets overview (Pytorch)
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Hugging Face Datasets overview (Tensorflow)
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What is dynamic padding?
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What happens inside the pipeline function? (PyTorch)
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What happens inside the pipeline function? (TensorFlow)
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Instantiate a Transformers model (PyTorch)
HuggingFace
Instantiate a Transformers model (TensorFlow)
HuggingFace
Preprocessing sentence pairs (PyTorch)
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Preprocessing sentence pairs (TensorFlow)
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Write your training loop in PyTorch
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Managing a repo on the Model Hub
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Chapter 1 Live Session with Sylvain
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Chapter 2 Live Session with Lewis
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The push to hub API
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Chapter 2 Live Session with Sylvain
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Chapter 3 live sessions with Lewis (PyTorch)
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Day 1 Talks: JAX, Flax & Transformers ๐ค
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Day 2 Talks: JAX, Flax & Transformers ๐ค
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Day 3 Talks JAX, Flax, Transformers ๐ค
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Chapter 4 live sessions with Omar
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Deploy a Hugging Face Transformers Model from S3 to Amazon SageMaker
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Deploy a Hugging Face Transformers Model from the Model Hub to Amazon SageMaker
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Run a Batch Transform Job using Hugging Face Transformers and Amazon SageMaker
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[Webinar] How to add machine learning capabilities with just a few lines of code
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Hugging Face + Zapier Demo Video
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Hugging Face + Google Sheets Demo
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Hugging Face Infinity Launch - 09/28
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Build and Deploy a Machine Learning App in 2 Minutes
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Hugging Face Infinity - GPU Walkthrough
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Otto - ๐ค Infinity Case Study
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Workshop: Getting started with Amazon Sagemaker Train a Hugging Face Transformers and deploy it
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Workshop: Going Production: Deploying, Scaling & Monitoring Hugging Face Transformer models
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๐ค Tasks: Causal Language Modeling
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๐ค Tasks: Masked Language Modeling
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Chapters (20)
Intro
2:38
Lewis Tunstallโs Background
3:37
Natural Language Processing with Transformers
6:21
Deploying models into production
7:24
Transformers & ONNX format
8:29
OpenAI GPT-2 / Auto-generated text
10:51
Hugging Face Course
12:37
Machine Learning Applications
16:33
Large Scale Model Evaluation
17:49
Machine Learning Benchmarks
20:14
Common Machine Learning Mistakes
22:54
What would you do differently at the start of your career?
25:21
Best advice for someone looking to get into AI/ML?
26:22
Will AI take over the world?
27:42
When will robots be in homes everywhere?
29:18
DeepMind Podcast
31:08
Favorite Machine Learning Papers
33:56
What is the meaning of life?
35:47
Checkout Lewisโs Natural Language Processing with Transformers book
39:55
Where you can follow Lewis online
๐
Tutor Explanation
DeepCamp AI