Disclaimer Shroff Publishers do not endorse the preview pages of kindle linked to our ISBNs. All Indian Reprints of Learn Coding Fast are Printed in Grayscale. Have you always been curious about machine learning but do not know where to start. Or perhaps your new job requires you to learn machine learning but you are overwhelmed with all the information available online. What is machine learning? What is Scikit-Learn? What does the fit() method that you see on so many online tutorials do? Pre-Requisites The book assumes that you are familiar with basic Python, especially with the concept of object-oriented programming in Python. If you are not familiar, you can check out my introductory book "Learn Python in one day and Learn It Well (2nd Edition)". What this book offers? Complex concepts are broken down into simple steps and examples are carefully chosen to illustrate each concept. Mathematical concepts are explained without complicated notations and formulas. What you'll learn: What is Machine Learning What is supervised, unsupervised, and reinforcement learning How to use the NumPy and pandas library How to use matplotlib to plot charts What is the Scikit-Learn library? What do the fit() and transform() methods do How to pre-process our data How to use pipelines and column transformers to streamline our code How to evaluate our models What is a confusion matrix and how to interpret it What is regression, classification, and clustering What is the theory behind the linear regression, poly regression, decision tree, random forest, SVM, and k-means clustering algorithms How to do a grid search to find the best hyperparameters What is regularization How to reduce the dimensions of our dataset and more...