From 4dda6956c03d34f32e17201b9fb9d2e3f6388a64 Mon Sep 17 00:00:00 2001 From: Surbhi Goel Date: Wed, 10 Jul 2024 19:51:59 +0100 Subject: [PATCH] Added ML intro, Repo cloning, virtual env, colab/jupyternb slides --- slides/slides.qmd | 41 +++++++++++++++++++++++++++++++++++++++++ 1 file changed, 41 insertions(+) diff --git a/slides/slides.qmd b/slides/slides.qmd index 8b47ee3..19bab3d 100644 --- a/slides/slides.qmd +++ b/slides/slides.qmd @@ -129,6 +129,14 @@ Helping Today: # Part 1: Neural-network basics -- and fun applications. +## Machine learning + +- Machine learns underlying patterns and relations in given data to produce an output. + +- Machine learning is accomplished by learning a mathematical function that can represent the data. + +- Learning can be supervised, unsupervised, semi-supervised, self-supervised, reinforcement etc. + ## Fitting a straight line I {.smaller} - Consider the data: @@ -360,6 +368,39 @@ Image source: [3Blue1Brown](https://www.3blue1brown.com/topics/neural-networks) - I have never met anyone actually training models in C++; I find it a bit weird. - See the PyTorch website: [https://pytorch.org/](https://pytorch.org/) +## Getting to the Exercise + *Github Repository Cloning* + +- Navigate to +[https://tinyurl.com/ml-iccs-24](https://tinyurl.com/ml-iccs-24) +- Go to terminal and type in the below command +- `git clone https://github.com/Cambridge-ICCS/practical-ml-with-pytorch` + +## Using online platform +*Using Colab* + +`https://tinyurl.com/4arrjjt5` + +*Using Jupyter Notebook* + +- Download the repo from the [https://tinyurl.com/ml-iccs-24](https://tinyurl.com/ml-iccs-24) +- `cd ` +- `jupyter notebook` +- exercises/01_penguin_classification.ipynb + +## Creating virtual environment +*Installing with venv* + +- `python3 -m venv venv` +- `source venv/bin/activate` + +*Installing with conda* + +- `conda create -n ml-workshop "python>=3.9.10"` +- `conda activate ml-workshop` +- `cd practical-ml-with-PyTorch` +`pip install . ` + # Other resources