{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# unit 1.9 - Neural Networks: what is next in this course?\n", "\n", "So far in this course we have covered the material:\n", "\n", "- introduction to machine learning\n", "- artificial neural networks, neurons\n", "- multi-layer perceptrons, stacks of linear layers and non-linearities\n", "- back-propagation and gradient descent\n", "- professional training scripts\n", "\n", "What is next in this course?\n", "\n", "## Units 2, 3, 4\n", "\n", "We will study neural networks for sequences of data, such as word in a sentence. We will quickly learn how to build our own state-of-the-art word and language models and try to replicate ChatGPT and similar. We will learn more complex neural network architectures such as convolutions and Transformers.\n", "\n", "## Unit 5\n", "\n", "We will take an overview on neural networks building blocks and popular and historic neural architectures.\n", "\n", "## Units 6, 7, 8\n", "\n", "We will look into more advanced deep learning and neural networks topics, such as non-supervised learning, advanced models of the brain and general artificial intelligence (AGI), reinforcement learning.\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "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": "3.11.6" } }, "nbformat": 4, "nbformat_minor": 5 }