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