Welcome to AI50 – a collection of beginner-friendly and intermediate-level deep learning notebooks designed to introduce essential deep learning concepts and applications. Each Colab notebook covers a specific topic with hands-on examples.
Tensorflow Playground Tensorflow Projector OpenCV for Beginners
Explore and experiment with deep learning fundamentals using the following notebooks:
Tensor operations, math and dataset loading in Tensorflow.
Learn the basics of regression, a supervised learning approach for predicting continuous outputs.
An introduction to image classification using a simple neural network model.
Dive deeper into image classification with Convolutional Neural Networks (CNNs) for improved accuracy and performance.
Learn to leverage pre-trained models for new tasks through transfer learning and finetuning techniques.
5. An Unhealthy Obsession with Autoencoders: Unsupervised Algorithms for Image Denoising and Anomaly Detection
How can a deep neural network learn without supervision? And how does it change the industries?
Introduction to text classification using neural networks for Natural Language Processing (NLP) tasks.
Explore Recurrent Neural Networks (RNNs) for handling sequential data in text classification tasks.
Experiment with RNNs for generating text sequences, training models to predict and produce text based on patterns in the data.
Apply deep learning to recognize basic audio signals, using convolutional networks for audio classification.
Each notebook can be accessed and run directly in Google Colab, allowing you to explore and experiment with code in a cloud-based environment.
To get started, simply click on any of the links above. Make sure you have a Google account to save your work on Colab.
Happy Learning!