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Machine learning with Python

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  • Intro to Machine Learning with Python
  • Machine Learning with Python
  • Machine Learning Terminology
  • Evaluation Metrics
  • Data Representation and Visualization of Data
  • Available Data Sets in Sklearn
  • Artificial Datasets with Scikit-Learn
  • Train and Test Sets by Splitting Learn and Test Data
  • k-Nearest Neighbor Classifier in Python
  • k-Nearest-Neighbor Classifier with sklearn
  • Neural Networks Introduction
  • Separating Classes with Dividing Lines
  • A Simple Neural Network from Scratch in Python
  • Pereceptron class in sklearn
  • Neural Networks, Structure, Weights and Matrices
  • Running a Neural Network with Python
  • Backpropagation in Neural Networks
  • Training a Neural Network with Python
  • Softmax as Activation Function
  • Confusion Matrix in Machine Learning
  • Training and Testing with MNIST
  • Dropout Neural Networks in Python
  • Neural Networks with Scikit
  • A Neural Network for the Digits Dataset
  • Naive Bayes Classification with Python
  • Naive Bayes Classifier with Scikit
  • Introduction to Text Classification
  • Text Classification in Python
  • Natural Language Processing with Python
  • Natural Language Processing: Classification
  • Introduction to Regression with Python
  • Decision Trees in Python
  • Regression Trees in Python
  • Random Forests in Python
  • Boosting Algorithm in Python
  • Principal Component Analysis (PCA) in Python
  • Linear Discriminant Analysis in Python
  • Expectation Maximization and Gaussian Mixture Models (GMM)
  • Introduction to TensorFlow
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