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Week 3 - Intro Kaggle competition - EDA and baseline models with PyTorch

Learning and testing - a.k.a. don't do Bullshit Machine Learning

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Course session

https://drive.google.com/file/d/18VsrKSqNFaWeWsL24ULFrNnwpghpdwJZ/view?usp=sharingarrow-up-right

Walk-through

Hyperparameter experiment

The following notebook will show how to set up a hyperparameter experiment in plain PyTorch. More importantly it give you the results and enables you to analyze and play around

Kaggle

  • Introduction

  • Titanic

Solutions exercise MLP

Presentation from the participants of the MLP from Coursera

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To-do

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Watch the videos on the next page

Go through the following notebooks and complete the second one (assignment notebook):

The next task is to analyze the results of the hyperparameter experiment and create a small presentation on your findings(e.g. batch size of 16 with lr=0.2 seems to equal batch size of 1 with lr=0.01). Here is the notebook again:

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Run your own hyperparameter experiment

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Do your own EDA on the Titanic Dataset and/or look at other EDA notebooks from competitors. Make a final presentable EDA notebook.

Familiarize yourself with this PyTorch Tutorials:

Coursera Videos

Watch them all😊

  1. Motivation Diabetic Retinopathy

  1. Breakdown of the Convolution (1D and 2D)

  1. Core Components of the Convolutional Layer

  1. Activation Functions

  1. Pooling and Fully Connected Layers

  1. Training the Network

  1. Transfer Learning

Done!

Tutorial 5: Inception, ResNet and DenseNet — UvA DL Notebooks v1.2 documentationuvadlc-notebooks.readthedocs.iochevron-right
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Google Colabcolab.research.google.comchevron-right
Google Colabcolab.research.google.comchevron-right
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Google Colabcolab.research.google.comchevron-right
The first notebook
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Google Colabcolab.research.google.comchevron-right
The assignment notebook
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