Python Course

This is a personal repository to teach Python, Machine Learning and Deep Learning(Basics)

To use this repository you have to install Anaconda and use Jupyter Notebook

Clarification: the content of this repository is not entirely created by me, some codes are a compilation of multiple courses that I have done.

Content:

• Datasets

- Directory of multiple collected Datasets - Appen - ics

• Week 1 - Python Basics

- Variables types - Operators - Conditionals - Cycles

• Week 2 - Python Basics 2

- Functions - Dictionaries - List

• Week 3 - Python Intermediate

- Inheritance - Generators - Iterators - Modules - Try Closures - Serializer

• Week 4 - Intro Numpy

- Sets - Numpy

• Week 5 - data visualization and manipulation

- Pandas - Matplotlib - Seaborn - Bokeh

• Week 6 - Mathematics (Basics)

- Linear Algebra - Probability and Statistics (see repository)

• Week 7 - Intro Machine Learning

- Linear Regression - Polynomial Regression - Logistic Regression

• Week 8 - Classification

- Overfit Complexity - K Nearest Neighbor (KNN) - Decision Tree - Support Vector Machines (SVM)

• Week 9 - Classification 2

- K Means - DBSCAN - Recommender Systems - Reduction of dimensionality (PCA, IPCA, KPCA, Regularization)

• Week 10 - Advanced Methods

- Robust Regressions - Assembly Methods - Cross Validation and K Folds - Parametric Optimization - Save and load ML Models - Intro Deep Learning Part 1

• Week 11 - Intro Deep Learning

- Intro Deep Learning Part 2 - Deep Learning (Basic Theory) - Pytorch - Convolutional Neural Network

• Week 12 - NLP

- Natural Language Process - NLTK - Recurrent Neural Network

• Bonus

- Chatbot - Dog or Muffin