Building Machine Learning Models in Python with scikit-learn
The Python scikit-learn library is extremely popular for building traditional ML models i.e. those models that do not rely on neural networks. This Repo works through the mini process of BUilding Machine Learning Models in Python with scikit-learn, how to use scikit-learn Library, and how it can be used to build a variety of machine learning models. First, You will learn how to use libraries for working with continuous, categorical, text as well as image data. Next, It introduces the Ordinary Regression models, seeing how to implement specialized regression models such as Lasso and Ridge Regression using the scikit-learn libraries. Finally, in addition to supervised learning techniques, you will also understand and implement unsupervised models such as clustering using the mean-shift algorithm and dimensionality reduction using principal components analysis.
Software required: scikit-learn, Python 3.x.