Machine Learning Tokyo is an AI community dedicated to democratizing Machine Learning through Open Education, Open Source and Open Science. Led by Suzana Ilić.

Transformers with Lucas Beyer, Google Brain
56:20
Transformers with Lucas Beyer, Google Brain
MLT __init__ Session #17: LLM int8
26:49
MLT __init__ Session #17: LLM int8
Text-to-Image Generation – Deep Dive into DALL-E 2, Imagen, Parti, VQGAN with Jerry Chi
47:14
Text-to-Image Generation – Deep Dive into DALL-E 2, Imagen, Parti, VQGAN with Jerry Chi
AI at Scale in Rakuten’s Recommendation Systems with Phuc Le
1:11:45
AI at Scale in Rakuten’s Recommendation Systems with Phuc Le
A Practical Tutorial on Building Machine Learning Demos with Gradio
47:06
A Practical Tutorial on Building Machine Learning Demos with Gradio
MLT __init__ Session #16: SeamlessGAN
31:06
MLT __init__ Session #16: SeamlessGAN
DL with Python: Generative deep learning (Chapter 12)
1:09:13
DL with Python: Generative deep learning (Chapter 12)
Statistics: Estimators, asymptotic theory, and random variable convergence 2 with Michal Fabinger
1:05:20
Statistics: Estimators, asymptotic theory, and random variable convergence 2 with Michal Fabinger
Statistics: Estimators asymptotic theory and random variable convergence 1 with Michal Fabinger
1:23:44
Statistics: Estimators asymptotic theory and random variable convergence 1 with Michal Fabinger
Statistics: Dependence of random variables and conditional distributions 3 with Michal Fabinger
1:24:57
Statistics: Dependence of random variables and conditional distributions 3 with Michal Fabinger
Statistics: Dependence of random variables and conditional distributions 2 with Michal Fabinger
52:53
Statistics: Dependence of random variables and conditional distributions 2 with Michal Fabinger
Statistics: Dependence of random variables and conditional distributions 1 with Michal Fabinger
1:11:24
Statistics: Dependence of random variables and conditional distributions 1 with Michal Fabinger
DL with Python: Deep learning for text (Chapter 11 2/2)
1:01:18
DL with Python: Deep learning for text (Chapter 11 2/2)
DL with Python: Deep learning for text (Chapter 11 1/2)
1:01:21
DL with Python: Deep learning for text (Chapter 11 1/2)
Zero-to-1: How to start a career in ML
34:54
Zero-to-1: How to start a career in ML
MLT __init__ Session #15: Deep Learning on a Data Diet
35:45
MLT __init__ Session #15: Deep Learning on a Data Diet
DL with Python: Deep learning for Time series (Chapter 10)
57:43
DL with Python: Deep learning for Time series (Chapter 10)
Statistics: Shapes and Moments of Probability Distributions 2 with Michal Fabinger
57:38
Statistics: Shapes and Moments of Probability Distributions 2 with Michal Fabinger
Statistics: Shapes and Moments of Probability Distributions 1 with Michal Fabinger
51:33
Statistics: Shapes and Moments of Probability Distributions 1 with Michal Fabinger
MLT – Machine Learning Tokyo
1:36
MLT – Machine Learning Tokyo
DL with Python: Advanced deep learning for computer vision (Chapter 9)
57:23
DL with Python: Advanced deep learning for computer vision (Chapter 9)
DL with Python: Introduction to deep learning for computer vision (Chapter 8)
57:55
DL with Python: Introduction to deep learning for computer vision (Chapter 8)
DL with Python: Working with Keras: A deep dive (Chapter 7)
1:03:20
DL with Python: Working with Keras: A deep dive (Chapter 7)
DL with Python: Fundamentals of machine learning (Chapter 5)
57:18
DL with Python: Fundamentals of machine learning (Chapter 5)
DL with Python: Getting started with neural networks (Chapter 4)
55:49
DL with Python: Getting started with neural networks (Chapter 4)
Deep Learning with Python: Introduction to Keras and TensorFlow (Chapter 3)
1:00:14
Deep Learning with Python: Introduction to Keras and TensorFlow (Chapter 3)
Deep Learning with Python: Mathematical building blocks of neural networks (Chapter 2)
1:20:45
Deep Learning with Python: Mathematical building blocks of neural networks (Chapter 2)
A rigorous introduction to probability theory: Lecture 4 with Michal Fabinger
55:32
A rigorous introduction to probability theory: Lecture 4 with Michal Fabinger
Deep Learning with Python: What is deep learning? (Chapter 1)
52:16
Deep Learning with Python: What is deep learning? (Chapter 1)
A rigorous introduction to probability theory: Lecture 3 with Michal Fabinger
51:37
A rigorous introduction to probability theory: Lecture 3 with Michal Fabinger