From 64c885474180531e9a42a73707db18d90726f34e Mon Sep 17 00:00:00 2001 From: "Carlos A. Iglesias" Date: Thu, 3 Apr 2025 18:41:49 +0200 Subject: [PATCH] Update 2_5_1_Exercise.ipynb --- ml4/2_5_1_Exercise.ipynb | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/ml4/2_5_1_Exercise.ipynb b/ml4/2_5_1_Exercise.ipynb index 331b1e1..a1937cc 100644 --- a/ml4/2_5_1_Exercise.ipynb +++ b/ml4/2_5_1_Exercise.ipynb @@ -56,7 +56,7 @@ "metadata": {}, "source": [ "# Genetic Algorithms\n", - "In this section, we are going to use the library DEAP [References](#References) for implementing a genetic algorithms.\n", + "In this section, we are going to use the library [DEAP](https://github.com/DEAP/deap/tree/master) for implementing a genetic algorithms.\n", "\n", "We are going to implement the OneMax problem as seen in class.\n", "\n", @@ -217,7 +217,7 @@ "source": [ "## Optional. Optimizing an ML pipeline with a genetic algorithm\n", "\n", - "The library [TPOT](#References) optimizes ML pipelines and comes with a lot of [examples](https://epistasislab.github.io/tpot/examples/) and even notebooks, for example for the [iris dataset](https://github.com/EpistasisLab/tpot/blob/master/tutorials/IRIS.ipynb).\n", + "The library [TPOT](https://epistasislab.github.io/tpot/latest/) optimizes ML pipelines and comes with a lot of [examples](https://epistasislab.github.io/tpot/examples/) and even notebooks, for example for the [iris dataset](https://github.com/EpistasisLab/tpot/blob/master/tutorials/IRIS.ipynb).\n", "\n", "Your task is to apply TPOT to the intermediate challenge and write a short essay explaining:\n", "* what TPOT does (with your own words).\n",