Python Machine Learning: The Ultimate Beginner’s Guide to Learn Python Machine Learning Step by Step using Scikit-Learn and Tensorflow

Length: 163 pages
Edition: 1
Language: English
Publication Date: 2022-01-14
ISBN-10: B09QJ2G3Q1
ISBN-13: 9798786210850
Sales Rank: #0 (See Top 100 Books)

Are you a beginner programmer looking to learn Python Machine Learning? Are you concerned about how to transfer what you already know into Python?

If so, this book will help you in overcoming such challenges.

As machines get more sophisticated and handle more and more work to free up human time, new ideas arise to help us improve their efficiency and abilities.

in Python Machine Learning: The Ultimate Python Machine Learning Beginner’s Guide Using Scikit-Learn and Tensorflow, you will gradually uncover knowledge and guidance on:

What exactly is machine learning
How to use Scikit-Learn & Tensorflow
The 5 V’s of Big Data
Neural networks with Scikit-learn
Machine learning & the Internet of Things (IoT)
How to Implement KNN Algorithm
How to Determine the “k” Parameter
And so much more…

This book was developed primarily for novices, and the basic, step-by-step directions and plain language make it an excellent place to begin for anybody with an interest in this fascinating topic. Python is a very great system that can give you with almost limitless options once you begin learning about it.

Introduction
    What is Machine Learning?
        The Difference Between Machine Learning (ML) and Artificial Intelligence (AI)
        Some Acronyms to be Aware of When Learning ML:
    Classification of Machine Learning Algorithms
    What is Scikit Learn?
    What is Tensorflow?
Chapter 1: History of Machine Learning
Chapter 2: Approaches to Machine Learning
    Machine Learning Terminology
    The Machine Language Process
Chapter 3: Machine Learning Environment Setup
    Setting Up Python and Anaconda
        Installing Python
        Setting Up the Python Environment
        Installing Anaconda
        Setting Up the Anaconda Environment
    Installing Scikit-Learn
    Installing TensorFlow
Chapter 4: Using Scikit-Learn
    The Learning Problem
    Loading Data Sets
    Regression
Chapter 5: K-Nearest Neighbors (KNN) Algorithm
    How to Determine the “k” Parameter
        How to Choose the Value of k?
        When to Use KNN Models?
        How the KNN Algorithm Works
    The Workings of the KNN Algorithm
    Implementing KNN Algorithm
Chapter 6: Using TensorFlow
    Getting Started with TensorFlow
        Working with TensorFlow Variables, Constants, Strings, Updates, Sessions, Placeholders, and Arrays
        Working TensorFlow Data Flow Graph and Programming Structure
Chapter 7: Machine Learning and Neural Networks
    Neural Networks
Chapter 8: Machine Learning and Big Data
    The 5 V’s of Big Data
    Big Data Uses
Chapter 9: Machine Learning Classification and Regression
Chapter 10: Machine Learning and the Cloud
    Benefits of Cloud-Based Machine Learning
Chapter 11: Machine Learning and the Internet of Things (IoT)
    Uses for the Internet of Things
    IoT Security Concerns
Chapter 12: Machine Learning and Robotics
    Robotic Learning
    Examples of Industrial Robots and Machine Learning
    Neural Networks with Scikit-learn
Chapter 13: Machine Learning Models
    Machine Learning and Swarm Intelligence
Chapter 14: Applications of Machine Learning
Chapter 15: Limitation of Machine Learning
    Problematic Limitation of Machine Learning
    Philosophical Objections and Limitation to Machine Learning
Chapter 16: Machine Learning and the Future
Conclusion
References
    Images