> For the complete documentation index, see [llms.txt](https://opencampus.gitbook.io/opencampus-machine-learning-program/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/archive/intermediate-machine-learning-legacy/week-1.md).

# Week 1 - Course Introduction

## Course session

**Welcome and Introduction round**

Introduction of the course, opencampus, the course instructor and the course participants

**Tool Set-Up**

* Coursera
* Colab
* Editor (VSCode)
* Virtual Environments
* Git/Github

**Walk-through**

PyTorch 101 (Lab 01)

{% embed url="<https://colab.research.google.com/drive/1C8Kq3xfdI5gSqy_3U9ZBQCVi8hjQRHNE?usp=sharing>" %}

A visual overview of the workflow in the Colab notebook you can get in the PyTorch diagram below:

{% file src="/files/njpPiERbx0BBrKq5sfCk" %}

## **To-do**

😊

1. Watch the following introduction video to the PyTorch framework

{% embed url="<https://www.youtube.com/watch?v=Uv0AIRr3ptg>" %}

2. Watch **Week 1** of the Coursera Course

{% embed url="<https://www.coursera.org/learn/machine-learning-duke>" %}

3. Go for your **own** through the Colab Notebook above (Pytorch101) and try to **understand and repeat** the steps for your own. Thereby you should also solve Task 1-3 in the notebook. You can create therefore a copy of the notebook in your Drive or download the notebook to work locally on it. Ensure that you sufficient computing resources available (i.e gpu) if you choose to work locally.

😊😊

Try to **improve the accuracy** in the PyTorch 101 notebook by tweaking the amount of layers and number of neurons

😊😊😊

Familiarize yourself with basic PyTorch Tutorials:

* <https://pytorch.org/tutorials/beginner/deep_learning_60min_blitz.html> (First part)
* <https://uvadlc-notebooks.readthedocs.io/en/latest/tutorial_notebooks/tutorial2/Introduction_to_PyTorch.html>


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