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Machine Learning With Python For Beginners A Step-By-Step Guide with Hands-On Projects

      Author: Baturi   |   16 August 2021   |   comments: 0



Machine Learning With Python For Beginners A Step-By-Step Guide with Hands-On Projects
Machine Learning With Python For Beginners: A Step-By-Step Guide with Hands-On Projects (Learn Coding Fast with Hands-On Project) by Jamie Chan
English | August 3, 2021 | ISBN: N/A | ASIN: B09BT7YCCM | 218 pages | EPUB | 1.77 Mb
A Step-By-Step Beginner's Guide to Machine Learning


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?
Does machine learning seem like a black-box to you?
This book is for you.
You no longer have to spend hours watching videos online or reading through tutorials that assume you are familiar with essential scientific and machine learning libraries in Python. This book answers all the questions above and more.
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)" available at
https://www.amazon.com/dp/1546488332
.
What this book offers?
Machine Learning for Beginners
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.
Hands-On Approach
Countless examples are provided for you to try out in each chapter, so that you can understand exactly what different machine learning methods do.
Systematic Approach
A systematic approach is taken to provide you with the background knowledge needed before covering advanced concepts.
How is this book different?
The best way to learn anything is by doing.
This book includes three hands-on projects at the end of the book for you to apply and practice all the concepts taught previously.
Working through the projects will not only give you an immense sense of achievement, it'll also help you retain the knowledge and solidify your understanding.
Whether you are an aspiring data scientist or just curious about machine learning, the book is designed to help you grasp the fundamental concepts of machine learning in a systematic and step-by-step fashion.
Are you ready to dip your toes into the exciting world of Machine Learning? This book is for you. Click the "Add to Cart" button to buy it now.
What you'll learn:What is Machine LearningWhat is supervised, unsupervised, and reinforcement learningHow to use the NumPy and pandas libraryHow to use matDescriptionlib to Description chartsWhat is the Scikit-Learn library?What do the fit() and transform() methods doHow to pre-process our dataHow to use pipelines and column transformers to streamline our codeHow to evaluate our modelsWhat is a confusion matrix and how to interpret itWhat is regression, classification, and clusteringWhat is the theory behind the linear regression, poly regression, decision tree, random forest, SVM, and k-means clustering algorithmsHow to do a grid search to find the best hyperparametersWhat is regularizationHow to reduce the dimensions of our datasetand more...
Finally, you'll be guided through three hands-on projects that require the application of all the topics covered.


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