Machine Learning with Python: The Ultimate Guide for Absolute Beginners with Steps to Implement Artificial Neural Networks with Real Examples (Useful Python Tools eg. Anaconda, Jupiter Notebook)
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Do want to learn how machine learning and neural networks work quickly and simply? Do you want to know how to build a machine learning model and you have no programming skill? Do you want to get started with learning data science?
This book is going to guide you to the basics and the principles behind machine learning. Machine learning is an active research domain and includes several different approaches. This book is going to help you understand the different approaches of machine learning and neural networks. It will guide you through the steps you need to build a machine learning model.
Machine learning implies programming. This book will teach you Python programming. This book does not require any pre-programming skills. It will help to get you started in Python programming, as well as how to use Python libraries to analyze data and apply machine learning.
Overall, this book is a go-to guide for getting started in machine learning modeling using Python programming. Once you get through the book, you will be able to develop your own machine learning models using Python.
Through this book, you will learn:
• Principles of machine learning
• Types of machine learning: supervised, unsupervised, semi-supervised, and reinforcement learning
• Advantages of each type of machine learning
• Principle and types of neural networks
• Steps to develop and fit artificial neural network model
• Getting started and installing Python
• Tools and platforms for Python programming
• How to use pandas, NumPy and matplotlib Python libraries
• How to develop a simple linear and logistic machine learning model
• How to develop and train a multi-layer artificial neural network two ways: from scratch and using the Python libraries
Even if you don’t have any background in machine learning and Python programming, this book will give you the tools to develop machine learning models.
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If you have already developed a relatively profound understanding with the python programming language, and are now looking to apply this skill set specifically towards machine and deep learning in finance, this guide is for you. Throughout the book, the author outlines a couple detailed scenarios in which he applies different types of machine and deep learning algorithms towards real life , financial market scenarios to help best bridge the connection between python and how it is being…
I read this book with big interest. This is really an excellent book. The book itself is a fairly quick read and can be tackled in an afternoon if it keeps your interest and the visual examples and clear instructions made the rest of the book a breeze to follow. Although it was easy to follow, I donât feel like I lost out on technical content an for a high-level introduction, it was concise and detailed and it was entertaining and highly educational and i especially appreciated the effort made…
This refreshed and extended version of python AI is an absolute necessity have for each individual required with handy AI. I am glad to peruse this book. Subsequent to perusing this book I learn numerous things. Avery elegantly composed book. Particularly simple begin in the event that you as of now have Anaconda stacked which incorporates Jupyter and Python as a matter of course. This book is a voyage through Machine Learning. In the event that you are a finished apprentice on the theme,…