# README

## Python Fundamental and Machine Learning

A Topic of Interest Group in Macao Polytechnic Institute

### Introduction

Lecturer: Steve Yan

Location: Macao Polytechnic Institute

Time Schedule: To be announced

Semester: 2

## Useful URLs

Typora: [typora.io](https://typora.io) ![](https://img.shields.io/badge/Web-.md-red)

Google Colab: [google/colab](https://colab.research.google.com) ![](https://img.shields.io/badge/Web-Python-green)

Kaggle: [kaggle](https://kaggle.com) ![](https://img.shields.io/badge/Web-Kaggle-blue)

### Course Outline

This lecture contains two parts, namely Python fundamental and Machine Learning. Moreover, all of the process will be running on the Linux machine, which means that it will contain the part of knowledge in Linux shell.

No slides are distributed (cuz. I do not regard slides as efficient format to display codes) but all of the codes and explanations are showed on this Repository as well as the official website [pyml.aspires.cc](https://app.gitbook.com/o/eOIzhSi31AT8uXcGbb1G/s/HAdGlEt8QdrT03dbqZCM/) of this lecture.

**Following topics will be covered in the Interest Group**

* Work with Linux
  * Hello Linux
  * Command Line
  * Vim
* The Python language
  * conda: the Python environment manager
  * Transfer to Python
  * File structure
  * Importing modules
  * pip: Package manager
  * DS Utilities: Numpy
* Traditional Machine Learning Algorithms
  * Supervised Learning
    * Linear and Polynomial Regression
    * K Neareast Neighborhood (KNN)
    * Naive Bayes Classifier
    * Neural Networks
  * Unsupervised Learning
    * K-means Clustering
* Concept of Deep Learning
  * Implementation of Neural Networks from scratch
  * Introduction to Tensorflow / PyTorch
  * CNN: NN with image processing
  * Introduction to Data Augmentation
  * Brief introduction to miscellaneous Neural Networks


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