Carnegie Mellon University Deep Learning

S24 Recitation 0O: Workflow of Homeworks

S18 Sequence to Sequence models: Attention Models

11-785 Spring 2023 Recitation 6: CNNs: Classification

Recitation 0E | Setting Up AWS Deep Learning AMI

Lecture 8 | Batch Normalization, Dropout and other Regularization methods

Lecture 17: Connectionist Temporal Classification (CTC), Sequence To Sequence Prediction

Fall 2024 Recitation 0E - Pytorch Part 1

Lecture 21: Variational Autoencoders

IDL Spring 2024: Lecture 25

Fall 2024 Recitation 0P - Cheating

11-785 Spring 2023 Recitation 0G: Debugging and Visualisation (Part 2/3)

Fall 2024 Recitation - 0W BlockProcessing

Fall 2024 Recitation 0Q - Workflow of HWs

Fall 2024 Recitation 0B - OOP Fundamentals Part 2

Fall 2024 Lecture 2

Fall 2024 - Lec 5

Lecture 7 | Acceleration, Regularization, and Normalization

IDL Spring 2024: Lecture 24

IDL Spring 2024: Lecture 14

F23 Lecture 15: Recurrent Networks, Part 3

S18 Lecture 26: Sequence to Sequence Models (Guest Lecture)

Spring 2025 Recitation 0.2 NumPy Fundamentals & JAX Part 1

Fall 2024 Recitation 0N - Debugging (Part 3)

Fall 2024 Recitation 0H - Google Cloud Part 2

Fall 2024 Recitation 0X - Paper to Code

Fall 2024 Recitation 0A - Python Fundamentals Part 2

Recitation 0b | Fundamentals of Numpy - Installing and Initializing arrays (1/8)

Fall 2024 Recitation 0B - OOP Fundamentals Part 1

Fall 2024 Recitation 0U - Writing a Report

IDL Spring 2024: Lecture 23

Fall 2024 Recitation 0C - Numpy Fundamentals Part 2

Recitation0-F: Debugging in Deep Learning - 1 by Akshat G.

(Old) Lecture 3 | Perceptrons and Gradient Descent

S24 Recitation 0O: Workflow of Homeworks

11-785 Spring 23 Lecture 6: Neural Networks: Optimization Part 1

(Old) Recitation 0 (2/2) | NumPy and PyTorch

11-785 Deep Learning Recitation 0B: Fundamentals of NumPy (Part 1/7)

11-785 Spring 23 Lecture 5b: Learning the Network Part 2

11-785 Spring 23 Lecture 9: Shift invariance and Convolutional Neural Networks

11-785 Spring 23 Lecture 5: Learning the Network

F23 Lecture 12: Deep Neural Networks, Convolutional Networks IV

Recitation 0b | Fundamentals of Numpy - Intro (1/8)

11-785 Spring 23 Lecture 17: Language Models and Sequence to Sequence Prediction

Fall 2024 Recitation 0T - Flow of the Project

Fall 2024 Recitation 0I - AWS

F23 Recitation 0K: Data Preprocessing (Part 1)

11785 Team 18 Reverse Dictionary Video

Lecture 19 | Representations and Autoencoders

Lecture: Graph Neural Networks

S24 Bootcamp 4 Part 1

Recitation 0b | Fundamentals of Numpy - Squeezing and Unsqueezing Arrays (6/8)