lectures.md

layout	title
page	Lectures

Lecture 01 (06 Sep)

• Course Introduction [PDF]
• References:
  • Think Python 2nd Edition
  • The Python (3.6) Tutorial

Lecture 02 (13 Sep)

• Introduction to Machine Learning [PDF]
• References:
  • scikit-learn Tutorials
  • Machine Learning Yearning by Andrew Ng

Lecture 03 (20 Sep)

• Text Classification (1) [PDF]
• Notebooks:
  • Text classification using logistic regression
  • Text classification using naive Bayes classifier
  • SMS Spam Classification
• References:
  • Working with Text Data - scikit-learn
  • Natural Language Processing with Python

Lecture 04 (27 Sep)

• Text Classification (2) [PDF]
• References:
  • Word2Vec Tutorail
  • Text Understanding from Scratch. Xiang Zhang, Yann LeCun. 2015.
  • fasText by Facebook Research

Lecture 05 (11 Oct)

• Recommender Systems [PDF]
• References:
  • Google News Personalization: Scalable Online Collaborative Filtering. Das et al., 2007.
  • Amazon.com Recommendations: Item-to-Item Collaborative Filtering. Linden et al., 2003.
  • Browsemap: Collaborative Filtering at LinkedIn
  • Building Large Scale Real World Recommender Systems (Netflix)
  • Gradient Descent Example (Jupyter Notebook)
  • User-based Collaborative Filtering (Jupyter Notebook)

Lecture 06 (18 Oct)

• Image Classification [PDF]
• References:
  • Training a Classifier - PyTorch
  • Image Classification Practical (CNN Version) by Oxford VGG
  • ImageNet

Lecture 07 (25 Oct)

• Network Programming [PDF]
• Sample Scripts:
  • TCP Server, TCP Client
  • UDP Server, UDP Client

Lecture 08 (01 Nov)

• Concurrent Programming (1) [PDF]
• Sample Scripts:
  • Daemonic Threads
  • Multithreaded Server
  • Multiprocess Server
  • Logging Thread Names

Lecture 09 (08 Nov)

• Concurrent Programming (2) [PDF]
• Sample Scripts:
  • Non-blocking TCP Server
  • Image downloading using aiohttp
• References
  • Async IO in Python: A Complete Walkthrough
  • AIOHTTP - Documentation

Lecture 10 (15 Nov)

• Web Server and Applications [PDF]
• Sample Scripts:
  • HTTP on TCP
  • HTTP using requests
  • Hello World Web Application using Flask
  • Query String and JSON Response in Flask

Lecture 11 (22 Nov)

• Asynchronous Tasks and Message Queues [PDF]
• Sample Scripts:
  • Redis Publisher, Subscriber
  • Celery Task, App

Lecture 12 (29 Nov)

• Deploying & Scaling Machine Learning Applications [PDF]

Lecture 13 (13 Dec)

• Final Examination