/Machine-Learning-A-Z-Python-Udemy

Machine Learning Algorithms in Python by SuperDataScience Team on Udemy

Primary LanguageJupyter Notebook

Machine Learning A-Z™: Hands-On Python

This course has been designed by Professional Data Scientists. Complex theory, algorithms and coding libraries are explained in a simple way.

Course Website

Content covered

  • Part 1 - Data Preprocessing
  • Part 2 - Regression:
    1. Simple Linear Regression
    2. Multiple Linear Regression
    3. Polynomial Regression
    4. SVR, Decision Tree Regression
    5. Random Forest Regression
  • Part 3 - Classification:
    1. Logistic Regression
    2. K-NN, SVM
    3. Kernel SVM
    4. Naive Bayes
    5. Decision Tree Classification
    6. Random Forest Classification
  • Part 4 - Clustering:
    1. K-Means
    2. Hierarchical Clustering
  • Part 5 - Association Rule Learning:
    1. Apriori
  • Part 6 - Reinforcement Learning:
    1. Upper Confidence Bound
    2. Thompson Sampling
  • Part 7 - Natural Language Processing:
    1. Bag-of-words model algorithms for NLP
  • Part 8 - Deep Learning:
    1. Artificial Neural Networks
    2. Convolutional Neural Networks
  • Part 9 - Dimensionality Reduction:
    1. PCA
    2. LDA
    3. Kernel PCA
  • Part 10 - Model Selection & Boosting:
    1. k-fold Cross Validation
    2. Parameter Tuning
    3. Grid Search
    4. XGBoost