Machine Learning with Python for Beginners

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…