Program Structure

• Siraj’s videos
  •    Short introductory video
  •     One hour live session
• Additional lesson(s) from Mat & other Udacity experts

Projects

A project every four weeks:
P1: Your First Neural Network “Bike Rentals”
P2: Object Recognition Neural Network
P3: Recurrent Neural Network “Generate Scripts”
P4: Realtime Translation Chatbot
P5: Generative Adversarial Network (GAN) “Create Human Faces”

Weekly Syllabus

Week 1: Types of Machine Learning : Neural Networks (NNs) & Linear Regression

Week 2: Cloud Computing + Sentiment Analysis : Text Classification

Week 3: Recommendation Systems + Math Notation : Algebra, Calculus, Matrix Math.

Week 4: Data Preparation : Right Data, Cleaning, Regularization, Dimensionality Reduction

Week 5: Drone Image Tracking : Convolutional Neural Networks (CNNs)

Week 6: Stock Prediction : Recurrent Neural Networks  (RNNs)

Week 7: Art Generation : Transfer Learning

Week 8: Music Generation : LSTMs Applied to Audio

Week 9: Poetry Generation : LSTMs Applied to NLP

Week 10: Language Translation : Sequence to Sequence

Week 11: Chatbot QA System with Voice : Sequence to Sequence in-depth

Week 12: Game Bot 2D : Reinforcement Learning via Monte-Carlo tree search

Week 13: Image Compression : Autoencoders

Week 14: Data Visualization : Anomaly Detection Results in 2D and 3D

Week 15: Image Generation : Generative Adversarial Networks

Week 16: One-shot Learning : Probabilistic Programming

WEEK1

• Regression Models
  • Scikit-Learn
• Intro to Neural Networks
  • Perceptrons
  • Train Networks
• Your First Neural Network
  • Numpy

Needed Tools

Numpy
For working with data

Pandas
For working with data

Matplotlib
For making visulizations

Anaconda
A package and environment manager for Data Science

Jupyter
Notebooks used to develop code