You can download the lectures here. We will try to upload lectures prior to their corresponding classes.

  • Lec1 - Intro to Computer Vision
    Summary: Briefly go about Computer Vision

  • Lec2 - Linear Classifiers and Perceptron
    Summary: Basics of Supervised Learning, Classification and the Perceptron Algorithm

  • Lec3 - Multilayer Perceptron and Intro to Deep Learning
    Summary: Evolving the perceptron model into Multiclas and Multilayer Perceptrons

  • Lec4 - Optimization and Regularization
    Summary: Gradiente Descent, Modern Optimizers and Regularizers

  • Lec5 - Pytorch I – MLPs
    Summary: Tensors, AutoDiff, MLP in Pytorch

  • Lec6 - Pytorch II – Images and Regularization
    Summary: Using images, batch normalization and dropout in Pytorch

  • Lec7 - Convolutional Neural Networks
    Summary: Convolution operation, Representation Learning with CNNs

  • Lec8 - Data Augmentation and Deep CNNs
    Summary: Data Transferormation and VGG nets

  • Lec9 - Transfer Learning and Residual Nets
    Summary: Transfer Learning/Fine Tunning with VGG and Resnets

  • Lec10 - Inception Net and what CNNs learn
    Summary: Branching Nets, 1x1 convolution, Inception, Deep Dream

  • Lec11 - Adversarial Examples and Self-supervision
    Summary: Ways to break networks' results and learn without labels

  • Lec12 - Intro to MLOps
    Summary: DevOps pare Machine Learning pipelines

  • Lec13 - Intro to Object Detection
    Summary: Localization and Detection tasks, Naive Detection, RCNN

  • Lec14 - Fast Object Detection
    Summary: Fast and Faster RCNN and YOLO

  • Lec15 - Intro to Image Segmentation
    Summary: Semantic and Instance Segmentation, UNet and Mask-RCNN

  • Lec16 - Applications of Detection and Segmentation
    Summary: Pose and Keypoint Detection, Face Recognition, Gaze Estimation

  • Lec17 - Autoencoders
    Summary: Autoencoders and the tasks in CV that can be solved with them.

  • Lec18 - Image Generation with GANs
    Summary: Simple Generative Adversarial Networks and DCGAN

  • Lec19 - Advanced GANs
    Summary: Conditinal GANs and StyleGAN

  • Lec20 - The Attention Mechanism
    Summary: Go over attention and masked attention.

  • Lec21 - Transformers and ChatGPT
    Summary: Dive into the transformer architecture, its use in CV and in ChatGPT.

  • Lec22 - Image Generation by Prompt
    Summary: Contrastive Learning via CLIP and Stable Diffusion