Neural Networks and Deep Learning (Course 1)

Lecture 1 
09/26 
Advanced Lecture Topics:
 AI is the new electricity
 Details of the course

Handouts

Lecture 2 
10/03 
Advanced Lecture Topic: Deep Learning Intuition
 How to frame a machine learning problem?
 How to choose your loss function?
 Intuition behind various realworld application of deep learning.
Completed modules:
 C1M1: Introduction to deep learning
 C1M2: Neural Network Basics

Handouts
Required:
 Find partner(s) for your final project and sign up here (link coming soon)
Quizzes (due at 11am):
 Introduction to deep learning
 Neural Networks Basics
Programming Assignments (due at 11am)
 Python Basics with Numpy (Optional)
 Logistic Regression with a neural network mindset

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (Course 2)

Lecture 3 
10/10 
Advanced Lecture Topic:
 FullCycle of a deep learning project
 The Mathematics of Deep Learning (backpropagation, initialization, regularization)
Completed modules:
 C1M3: Shallow Neural Network
 C1M4: Deep Neural Networks

Handouts
Quizzes (due at 11am):
 Shallow Neural Networks
 Key concepts on Deep Neural Networks
Programming Assignments (due at 11am):
 Planar data classification with a hidden layer
 Building your Deep Neural Network: step by step
 Deep Neural Network  Application

Project Proposal Due 
10/14 Sunday 11:59PM 


Lecture 4 
10/17 
Advanced Lecture Topics:
 Attacking neural networks with Adversarial examples
 Generative Adversarial Networks
Completed modules:
 C2M1: Practical aspects of deep learning
 C2M2: Optimization algorithms

Handouts
Optional Video
 Batch Normalization videos from C2M3 will be useful for the inclass lecture.
Optional Reading
Quizzes (due at 11am):
 Practical aspects of deep learning
 Optimization Algorithms
Programming Assignments (due at 11am):
 Initialization
 Regularization
 Gradient Checking
 Optimization

Structuring Machine Learning Projects (Course 3)

Lecture 5 
10/24 
Advanced Lecture Topics:
 AI in Health Care (Guest Speaker: Pranav Rajpurkar)
 Livecell segmentation Case Study
Completed modules:
 C2M3: Hyperparameter Tuning, Batch Normalization
 C3M1: ML Strategy (1)
 C3M2: ML Strategy (2)

Handouts
Optional Reading
Quizzes (due at 11am):
 Hyperparameter tuning, Batch Normalization, Programming Frameworks
 Bird recognition in the city of Peacetopia (case study)
 Autonomous driving (case study)
Programming Assignments (due at 11am):

Midterm Review 
10/30 

Handouts

Convolutional Neural Networks (Course 4)

Lecture 6 
10/31 
Advanced Lecture Topic:
 Deep Learning Project strategy  Case studies
Completed modules:
 C4M1: Foundations of Convolutional Neural Network
 C4M2: Deep Convolutional Models

Handouts
Quizzes (due at 11am):
 The basics of ConvNets
 Convolutional models
Programming Assignments (due at 11am):
 Convolutional Neural Network  Step by Step
 Convolutional Neural Network  Application
 Keras Tutorial: This assignment is optional.
 Residual Networks

Midterm 
11/02 Friday 

Midterm Exam
 Date: November 02, 2018
 Time: 3pm  6pm
 Locations:
Last names AK: STLC 111 (Google Maps)
Last names LZ: Cubberley Auditorium (Google Maps)

Alternate Midterm 
11/05 Monday 

Alternate Midterm Exam
 Date: November 05, 2018
 Time: 6pm  9pm
 Location: 260113

Lecture 7 
11/07 
Advanced Lecture Topics:
 Interpretability of Neural Network
Completed modules:
 C4M3: ConvNets Applications (1)
 C4M4: ConvNets Applications (2)

Handouts
Optional Reading
Quizzes (due at 11am):
 Detection Algorithms
 Special Applications: Face Recognition and Neural Style Transfer
Programming Assignments (due at 11am):
 Car Detection with YOLOv2
 Art Generation with Neural Style Transfer
 Face recognition for the Happy House

Project Milestone Due 
11/09 Friday 11:59pm 


Sequence Models (Course 5)

Lecture 8 
11/14 
Advanced Lecture Topic:
 Career Advice
 Reading Research Papers
Completed modules:
 C5M1: Recurrent Neural Networks

Handouts
Optional Reading
Quizzes (due at 11am):
 Recurrent Neural Networks
Programming Assignments (due at 11am):
 Building a Recurrent Neural Network  Step by Step
 Dinosaur Land  Characterlevel Language Modeling
 Jazz improvisation with LSTM

Thanksgiving break (Enjoy!)

Lecture 9 
11/28 
Advanced Lecture Topics:
 Deep Reinforcement Learning
Completed modules:
 C5M2: Natural Language Processing and Word Embeddings
 C5M3: SequencetoSequence Models

Handouts
Optional Reading
Quizzes (due at 11am):
 Natural Language Processing and Word Embeddings
 Sequence Models and Attention Mechanism
Programming Assignments (due at 11am):
 Operations on Word Vectors  Debiasing
 Emojify!
 Neural Machine Translation with Attention
 Trigger Word Detection

Lecture 10 
12/05 
Advanced Lecture Topics:
 Conversational Assistants
 Class WrapUp

Handouts

Poster Session 
12/14 Friday 

Poster Session

Final Project Report Due 
12/16 Sunday, 11:59pm 

