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Different Perspective of Line Regression
Machine Learning #machine learning

Different Perspective of Line Regression

1. Line regression 1.1 Ordinary Least Squares (OLS) Perspective 1.1.1 Model Representation: The linear regression model is represented as: \hat{Y} = X

narcissuskid narcissuskid 发布于 2024-03-18

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2023 年 09 月

11.9. Large-Scale Pretraining with Transformers

2023-09-11

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Is it possible to fine-tune T5 using a minibatch consisting of different tasks? Why o
11.8. Transformers for Vision

2023-09-11

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. How does the value of img_size affect training time? The value of img_size affects th
11.7. The Transformer Architecture

2023-09-11

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Train a deeper Transformer in the experiments. How does it affect the training speed
11.6. Self-Attention and Positional Encoding

2023-09-11

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Suppose that we design a deep architecture to represent a sequence by stacking self-a
11.5. Multi-Head Attention

2023-09-10

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Visualize attention weights of multiple heads in this experiment. import sys import t
11.4. The Bahdanau Attention Mechanism

2023-09-10

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Replace GRU with LSTM in the experiment. import sys import torch.nn as nn import torc
11.3. Attention Scoring Functions

2023-09-10

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Implement distance-based attention by modifying the DotProductAttention code. Note th
11.2. Attention Pooling by Similarity

2023-09-09

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises 1. Parzen windows density estimates are given by \hat{p}(x)=\frac{1}{n}\sum_ik(x,x_i)
11.1. Queries, Keys, and Values

2023-09-09

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises import sys import torch.nn as nn import torch import warnings from sklearn.model_selecti
10.7. Sequence-to-Sequence Learning for Machine Translation

2023-09-07

Deep Learning #solutions#d2l#pytorch
github: https://github.com/pandalabme/d2l/tree/main/exercises import sys import torch.nn as nn import torch import warnings import numpy as np from sk
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