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MIT Introduction to Deep Learning 6.S191: Lecture 1 *New 2024 Edition* Foundations of Deep Learning Lecturer: Alexander Amini For all ...
YouTube-Alexander Amini
1か月前動画の見どころ1/13枚目 Introduction
動画の見どころ2/13枚目 Course information
動画の見どころ3/13枚目 Why deep learning?
動画の見どころ4/13枚目 The perceptron
動画の見どころ5/13枚目 Perceptron example
動画の見どころ6/13枚目 Applying neural networks
動画の見どころ7/13枚目 Loss functions
動画の見どころ8/13枚目 Training and gradient descent
動画の見どころ9/13枚目 Backpropagation
動画の見どころ10/13枚目 Setting the learning rate
動画の見どころ11/13枚目 Batched gradient descent
動画の見どころ12/13枚目 Regularization: dropout and early stopping
動画の見どころ13/13枚目 Summary
Learn about watsonx → https://ibm.biz/BdvxDm Get a unique perspective on what the difference is between Machine Learning and Deep Learning ...
YouTube-IBM Technology
2022/03/31AI & Machine Learning Bootcamp(US Only): ...
YouTube-Simplilearn
2019/06/03動画の見どころ1/10枚目 What Is Deep Learning?
動画の見どころ2/10枚目 Deep Learning vs Machine Learning
動画の見どころ3/10枚目 Working of Neural Networks
動画の見どころ4/10枚目 How does Deep Learning work?
動画の見どころ5/10枚目 Neurons
動画の見どころ6/10枚目 Applications of Deep Learning
動画の見どころ7/10枚目 Limitations of Deep Learning
動画の見どころ8/10枚目 Quiz
動画の見どころ9/10枚目 Deep Learning Frameworks
動画の見どころ10/10枚目 Conclusion
What are the neurons, why are there layers, and what is the math underlying it? Help fund future projects: ...
YouTube-3Blue1Brown
2017/10/05MIT Introduction to Deep Learning 6.S191: Lecture 1 Foundations of Deep Learning Lecturer: Alexander Amini 2023 Edition For all lectures, ...
YouTube-Alexander Amini
2023/03/10動画の見どころ1/14枚目 Introduction
動画の見どころ2/14枚目 Course information
動画の見どころ3/14枚目 Why deep learning?
動画の見どころ4/14枚目 The perceptron
動画の見どころ5/14枚目 Perceptron example
動画の見どころ6/14枚目 From perceptrons to neural networks
動画の見どころ7/14枚目 Applying neural networks
動画の見どころ8/14枚目 Loss functions
動画の見どころ9/14枚目 Training and gradient descent
動画の見どころ10/14枚目 Backpropagation
動画の見どころ11/14枚目 Setting the learning rate
動画の見どころ12/14枚目 Batched gradient descent
動画の見どころ13/14枚目 Regularization: dropout and early stopping
動画の見どころ14/14枚目 Summary
Course lectures for MIT Introduction to Deep Learning. http://introtodeeplearning.com. Play all · Shuffle · 1:09:58 · MIT Introduction to Deep Learning | 6.
YouTube-Alexander Amini
2018/02/05The second in a two-lecture series on our recently-announced Categorical Deep Learning framework (categoricaldeeplearning.com), ...
YouTube-Petar Veličković
1か月前Deep learning is a revolutionary technique for discovering patterns from data. We'll see how this technology works and what it offers us for ...
YouTube-ACMSIGGRAPH
2018/08/12But what is a neural network? | Chapter 1, Deep learning. 3Blue1Brown · 20:33 · Gradient descent, how neural networks learn | Chapter 2, Deep learning.
YouTube-3Blue1Brown
2017/10/17Learn the fundamental concepts and terminology of Deep Learning, a sub-branch of Machine Learning. This course is designed for absolute ...
YouTube-freeCodeCamp.org
2020/07/30動画の見どころ1/25枚目 Introduction
動画の見どころ2/25枚目 What is Deep Learning
動画の見どころ3/25枚目 Introduction to Neural Networks
動画の見どころ4/25枚目 How do Neural Networks LEARN?
動画の見どころ5/25枚目 Core terminologies used in Deep Learning
動画の見どころ6/25枚目 Activation Functions
動画の見どころ7/25枚目 Loss Functions
動画の見どころ8/25枚目 Optimizers
動画の見どころ9/25枚目 Parameters vs Hyperparameters
動画の見どころ10/25枚目 Epochs, Batches & Iterations
動画の見どころ11/25枚目 Conclusion to Terminologies
動画の見どころ12/25枚目 Introduction to Learning
動画の見どころ13/25枚目 Unsupervised Learning
動画の見どころ14/25枚目 Reinforcement Learning
動画の見どころ15/25枚目 Regularization
動画の見どころ16/25枚目 Introduction to Neural Network Architectures
動画の見どころ17/25枚目 Fully-Connected Feedforward Neural Nets
動画の見どころ18/25枚目 Recurrent Neural Nets
動画の見どころ19/25枚目 Convolutional Neural Nets
動画の見どころ20/25枚目 Introduction to the 5 Steps to EVERY Deep Learning Model
動画の見どころ21/25枚目 1. Gathering Data
動画の見どころ22/25枚目 2. Preprocessing the Data
動画の見どころ23/25枚目 3. Training your Model
動画の見どころ24/25枚目 4. Evaluating your Model
動画の見どころ25/25枚目 Conclusion to the Course
Learn PyTorch for deep learning in this comprehensive course for beginners. PyTorch is a machine learning framework written in Python.
YouTube-freeCodeCamp.org
2022/10/06Introduction
2. The number one rule of ML
6. What can deep learning be used for?
10. How to (and how not to) approach this course
14. Creating tensors
20. Matrix multiplication
27. Selecting data (indexing)
30. Accessing a GPU
35. Creating a dataset with linear regression
41. Checking out the internals of our model
45. PyTorch training loop intuition
54. Putting everything together
64. Turing our data into tensors
69. Loss, optimizer and evaluation functions for classification
76. Creating a straight line dataset
88. Troubleshooting a mutli-class model
95. TorchVision
103. Training and testing loops for batched data
112. Convolutional neural networks (overview)
118. Training our first CNN
126. Introduction to custom datasets
136. Creating image DataLoaders
143. Data augmentation
151. Plotting model 0 loss curves
157. Predicting on custom data
of the math or code. Deep Learning is an important subfield of Artificial Intelligence (AI) that connects various topics like Machine Learning ...
YouTube-DeepLearning.TV
2015/12/07... machine learning, and deep learning. Master Inventor, Martin Keen, makes some important points about neural networks and does it all in 5 ...
YouTube-IBM Technology
2022/05/24Learn how watsonx helps you utilize AI → https://ibm.biz/BdMpXV The recent interest in AI as meant a lot of people have been encountering ...
YouTube-IBM Technology
2023/09/18Share your videos with friends, family, and the world.
YouTube-DeepLearning.TV
2015/12/07Share your videos with friends, family, and the world.
YouTube-StatQuest with Josh Starmer
2024/04/08In this comprehensive exploration of the field of deep learning with Professor Simon Prince who has just authored an entire text book on ...
YouTube-Machine Learning Street Talk
2023/12/26Introduction
General Book Discussion
The Neural Metaphor
Back to Book Discussion
Emergence and the Mind
Computation in Transformers
Studio Interview with Prof. Simon Prince
Why Deep Neural Networks Work: Spline Theory
Overparameterization in Deep Learning
Inductive Priors and the Manifold Hypothesis
Universal Function Approximation and Deep Networks
Training vs Inference: Model Bias
Model Generalization Challenges
Purple Segment: Unknown Topic
Visualizations in Deep Learning
Deep Learning Theories Overview
Tricks in Neural Networks
Critiques of ChatGPT
Ethical Considerations in AI
When talking about artificial intelligence (AI), deep learning and machine learning are invariably mentioned in the same breath.
YouTube-IBM Developer
2020/04/30Purdue Post Graduate Program In AI And Machine Learning: ...
YouTube-Simplilearn
2023/11/12Share your videos with friends, family, and the world.
YouTube-CampusX
2010/09/23