These videos cover the basics of machine learning, using Python. We explain machine learning and its many uses, and then continue with creating models and predicting data using several supervised learning algorithms. You will master:
Concepts of machine learning, including the types of machine learning models such as Linear Regression, Decision Tree, and Nearest-Neighbors.
Start-to-end Machine Learning, including loading raw data from external sources, cleaning and converting data into desired formats, slicing the data into features and labels, slicing the data into training and testing datasets, instantiating machine learning models, fitting and transforming data into the models, testing the models against testing data, predicting values for new data, checking accuracy of the models, understanding and testing precision and recall, tuning the models, exporting fitted models, and importing them in other files.
Programming language, data structures and libraries, including Python 3+, Pandas, and Scikit-Learn.