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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)
  • 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