Master machine learning fundamentals in this full tutorial course for beginners. You will learn how to build robust machine learning models.

Machine Learning in Python - Full Tutorial Course for Beginners

The Python code notebooks and the used data are available at: https://github.com/AISPUBLISHING/python_mlbc

Here is what the course covers:

⌨️ Part 1: Data Preprocessing: Importing the Libraries and Dataset, Deal with Missing Data, Detecting outliers, Categorical Data, Splitting the Dataset into the Training set and Test Set, Feature Scaling, Data Preprocessing Template

⌨️ Part 2: Regression: Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, Support Vector Regression, Decision Tree Regression, Random Forest Regression, Evaluating Regression Models Performance

⌨️ Part 3: Classification: Lectures: Logistic Regression, K-Nearest Neighbors(K-NN), Support Vector Machine(SVM), Naïve Bayes, Decision Tree Classification, Random Forest Classification, Evaluating Classification Models Performance

⌨️ Part 4: Clustering: K-Means Clustering, Hierarchical Clustering, Recommender System

⌨️ Part 5: Dimensionality Reduction: Principle Component Analysis(PCA), Linear Discriminant Analysis(LDA) and Kernel PCA

⌨️ Part 6: Artificial Neural Network (with Keras): Data Preprocessing, Create the ANN, Making Predictions and Evaluating model performance

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Machine Learning Pipelines performs a complete workflow with an ordered sequence of the process involved in a Machine Learning task. The Pipelines can also