{ "cells": [ { "cell_type": "markdown", "id": "610a5a2e", "metadata": {}, "source": [ "[![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/aws-samples/aws-machine-learning-university-accelerated-tab/blob/master/MLU-MAIN.ipynb)" ] }, { "cell_type": "markdown", "id": "42951fd3", "metadata": {}, "source": [ "![MLU Logo](data/MLU_Logo.png)" ] }, { "cell_type": "markdown", "id": "ab8947dc", "metadata": {}, "source": [ "# Machine Learning University\n", "Welcome to the GitHub page of __Machine Learning University (MLU)__. Our mission is to make machine learning accessible to anyone, anywhere, anytime. We have courses available across many sub-domains of machine learning.\n", "## Getting Started\n", "There are just two steps to start your deep learning journey!\n", "### Step 1: Start Instance\n", "\n", "Choose `CPU` or `GPU` and click `Start instance`.\n", "First-time users without GPU experience\n", "are recommended to start with `CPU`.\n", "\n", "### Step 2: Copy to Project\n", "\n", "Click `Copy to project` and install the environment file (.yml).\n", "\n", "## Course List\n", "Learners have access to jupyter notebooks, slides and accompanying video lectures. See the MLU course list below.\n", "* ### [Natural Language Processing](https://github.com/aws-samples/aws-machine-learning-university-accelerated-nlp) [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/aws-samples/aws-machine-learning-university-accelerated-nlp/blob/master/notebooks/MLA-NLP-Lecture1-Text-Process.ipynb)\n", "This course is designed to help you get started with Natural Language Processing (NLP) and learn how to use NLP in various use cases. You can view the [GitHub](https://github.com/aws-samples/aws-machine-learning-university-accelerated-nlp) repository of this class for more details.\n", "* ### [Tabular Data](https://github.com/aws-samples/aws-machine-learning-university-accelerated-tab) [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/aws-samples/aws-machine-learning-university-accelerated-tab/blob/master/MLU-MAIN.ipynb)\n", "Learn how to get started with tabular data (spreadsheet-like data) and the widely used machine learning techniques to manipulate tabular data. See the [GitHub](https://github.com/aws-samples/aws-machine-learning-university-accelerated-tab) page for more info and hands-on notebooks.\n", "* ### [Computer Vision](https://github.com/aws-samples/aws-machine-learning-university-accelerated-cv) [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/aws-samples/aws-machine-learning-university-accelerated-cv/blob/master/notebooks/MLA-CV-DAY1-NN.ipynb)\n", "Through this course, you will gain the necessary skills to get started with computer vision and use it in practical problems. See the [GitHub](https://github.com/aws-samples/aws-machine-learning-university-accelerated-cv) page for more info.\n", "* ### [Decision Trees and Ensemble Methods](https://github.com/aws-samples/aws-machine-learning-university-dte) [![Open In Studio Lab](https://studiolab.sagemaker.aws/studiolab.svg)](https://studiolab.sagemaker.aws/import/github/aws-samples/aws-machine-learning-university-dte/blob/main/notebooks/lecture_1/DTE-LECTURE-1-PRUNE.ipynb)\n", "Get started with tree-based and ensemble models in this class. Visit the [GitHub](https://github.com/aws-samples/aws-machine-learning-university-dte) page to start learning." ] } ], "metadata": { "kernelspec": { "display_name": "conda_python3", "language": "python", "name": "conda_python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.13" } }, "nbformat": 4, "nbformat_minor": 5 }