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    Python Machine Learning For Beginners: Handbook For Machine Learning, Deep Learning And Neural Networks Using Python, Scikit-Learn And TensorFlow
    Python Machine Learning For Beginners: Handbook For Machine Learning, Deep Learning And Neural Networks Using Python, Scikit-Learn And TensorFlow
    Python Machine Learning For Beginners: Handbook For Machine Learning, Deep Learning And Neural Networks Using Python, Scikit-Learn And TensorFlow
    Ebook112 pages1 hour

    Python Machine Learning For Beginners: Handbook For Machine Learning, Deep Learning And Neural Networks Using Python, Scikit-Learn And TensorFlow

    By Finn Sanders

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    About this ebook

    Imagine a world where you can make a computer program learn for itself? What if it could recognize who is in a picture or the exact websites that you want to look for when you type it into the program? What if you were able to create any kind of program that you wanted, even as a beginner programmer, without all of the convoluted codes and other information that makes your head spin?


    This is actually all possible. The programs that were mentioned before are all a part of machine learning. This is a breakthrough in the world of information technology, which allows the computer to learn how to behave, rather than asking the programmer to think of every single instance that may show up with their user ahead of time. it is taking over the world, and you may be using it now, without even realizing it. 
    If you have used a search engine, worked with photo recognition, or done speech recognition devices on your phone, then you have worked with machine learning. And if you combine it with the Python programming language, it is faster, more powerful, and easier (even for beginners) to create your own programs today. Python is considered the ultimate coding language for beginners, but once you start to use it, you will never be able to tell. Many of the best programs out there use this language behind them, and if you are a beginner who is ready to learn, this is a great place to start. 
    If you have a program in mind, or you just want to be able to get some programming knowledge and learn more about the power that comes behind it, then this is the guidebook for you. 
     


    ★★Some of the topics that we will discuss include★★


    ♦ The Fundamentals of Machine Learning, Deep learning, And Neural Networks
    ♦ How To Set Up Your Environment And Make Sure That Python, TensorFlow And Scikit-Learn Work Well For You
    ♦ How To Master Neural Network Implementation Using Different Libraries
    ♦ How Random Forest Algorithms Are Able To Help Out With Machine Learning
    ♦ How To Uncover Hidden Patterns And Structures With Clustering
    ♦ How Recurrent Neural Networks Work And When To Use
    ♦ The Importance Of Linear Classifiers And Why They Need To Be Used In Machine Learning
    ♦ And Much More!



    This guidebook is going to provide you with the information you need to get started with Python Machine Learning. If you have an idea for a great program, but you don't have the technical knowledge to make it happen, then this guidebook will help you get started. Machine learning has the capabilities, and Python has the ease, to help you, even as a beginner, create any product that you would like. 
     


    If you want to learn more about how to make the best programs with Python Machine learning, buy the book today!

    LanguageEnglish
    PublisherFinn Sanders
    Release dateMay 22, 2019
    Python Machine Learning For Beginners: Handbook For Machine Learning, Deep Learning And Neural Networks Using Python, Scikit-Learn And TensorFlow

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    • 1/5

      Jul 7, 2020

      Reads like someone's poorly written term paper that was padded for length.Don't waste your time.

    Book preview

    Python Machine Learning For Beginners - Finn Sanders

    holder.

    Table of Contents

    Introduction

    Chapter 1: What is Machine Learning?

    Chapter 2: What is Deep Learning, Scikit-Learn and Tensor Flow?

    Chapter 3: The Basics of Python

    Chapter 4: Setting Up Your Environment

    Chapter 5: Getting Started with Scikit-Learn

    Chapter 6: K-Nearest Neighbors Algorithm

    Chapter 7: What is K-Means Clustering?

    Chapter 8: What are Support Vector Machines?

    Chapter 9: Bringing it Back to Scikit-Learn with Neural Networks

    Chapter 10: How the Random Forest Algorithm Can Help in Machine Learning

    Chapter 11: How Can I Use TensorFlow

    Chapter 12: Working with Recurrent Neural Networks

    Chapter 13: Linear Classifier

    Chapter 14: Other Processes You Can Use with Python Machine Learning

    Conclusion

    Introduction

    The following chapters will discuss everything that you need to know in order to get started with Python machine learning. There are a lot of different things that you will be able to do when you work with traditional forms of coding. These have been used for a long time to create programs, websites, and more. But with machine learning, you are able to take all of this to a new level. Machine allows for an element of artificial intelligence, ensuring that you are going to be able to find patterns, cluster information together, and do some amazing things in the process.

    Learning a new coding language used to be tricky. It could take years to master a code enough to write out some basic programs. And then add on machine learning, a process that allows a computer program to learn and do the work on its own, can take even longer. In the past, only those who had a lot of experience, and even education, could hope to do well with this part of the technological world. But with the help of this guidebook, anyone can learn how to use the Python coding language along with machine learning, and write their own programs in no time.

    This guidebook is going to take some time to explore machine learning and what it is all about. We will look at some of the basics of machine learning and the difference between supervised, unsupervised, and reinforcement machine learning. We will also take a look at some of the basic libraries that you can use with this machine learning, such as Scikit-learn and TensorFlow to help you have the tools that you need. And to finish up the beginning of this guidebook, we will take a look at some of the basics of Python and how to write a few codes that you can later use with machine learning.

    From here, we are going to take a look at some of the different things that you are able to do with Python machine learning. We will look at some things like K-Means clustering, support vector machines, random forests algorithms, recurrent neural networks, and even linear classifiers. All of these can be used in different situations based on what kind of program you would like to work with when you start machine learning.

    There is a big world that comes with machine learning, and when you use the Python programming language to help you see results, you are going to love all of the different coding and programming tools that you want. This guidebook is going to take a look at all of the different things that you are able to work with python machine learning, so you can start working with your own projects in no time.

    When you are ready to learn more about machine learning, and you want to be able to create some of your programs with the help of Python, make sure to check out this guidebook to help you get started.

    Chapter 1: What is Machine Learning?

    Before we start learning about some of the different parts that come with machine learning, and before we bring out some of the codes that are needed in order to be successful with machine learning, it is time to learn a bit about what machine learning is. machine learning is a type of artificial intelligence that is going to provide systems with the ability to learn from experience, without being programmed for everything that you need the process to do. Machine learning is going to be concerned with the development of computer applications that can access data and learn from it on themselves.

    This kind of learning process can begin with observations or data, like instructions, examples, and direct experience to find the right patterns out of the data, and to use these predictions to know what to do in the future. The main goal that you are going to see with machine learning is that it allows the computer to learn in an automatic manner, without any help or any intervention from humans, and the computer program can make the necessary adjustments as situations change.

    When you work with machine learning, you will find that it makes analyzing large quantities of data easier than even. Machine learning can give us some results that are profitable, but of course, you first have to learn how to set it up, and there are a few resources that are needed before you are able to make this all happen. This type of coding is often going to take a bit more time to work with because you are basically training the models of machine learning to do what you want, even when you aren’t there, which can really increase how much the system can do.

    There are a lot of different things that you are able to use machine learning for. Any time that you aren’t sure how the end result is going to turn up, or you aren’t sure what the input of the other person could be, you will find that machine learning can help you get through some of these problems. If you want the computer to be able to go through a long list of options and find patterns, or find the right result, then machine learning is going to work the best for you. Some of the other things that machine learning can help out with include:

    Voice recognition

    Facial recognition

    Search engines. The machine learning program is going to start learning from the answers that the individual provides, or the queries, and will start to give better answers near the top as time goes on.

    Recommendations after shopping

    Going through large amounts of data about finances and customers and making accurate predictions about what the company should do to increase profits and happy customers along the way.

    These are just a few of the examples of when you would want to start utilizing a program that needs to be able to act on its own. Many of the traditional programs that you are going to learn how to use as a beginner are going to be much simpler than this. They will tell the computer exactly what it should do in a given situation. This works great for a lot of programs, but for things like artificial intelligence, it is not going to be enough.

    With traditional coding, you will be able to figure out, or at least limit the choices, that the other person is going to give to you. And then you can add in a catch all at the end in cause the other person puts in something else. For example, if your program has the question "What is 2 + 2? You would then have a response to if they picked 4 as the answer, and then another answer to handle any other inputs that the user put into the system.

    But this doesn’t always work the best if you are working with some of the programs that work the best with machine learning. For example, if you are doing a search engine, you won’t be able to guess each and every query that the user is going to make. If you are using voice recognition on Alexa, you won’t be able to figure out each request, and how each dialect is going to sound to the machine, ahead of time. This is why machine learning can come into play and is so important.

    The importance of Python

    While we will take a look at Python and how it works in a bit, it is important to note that Python is one of the best languages to work with when it comes to machine learning. Python is a simple language, one that is easy enough for beginners to the world of programming to work with. Yet it still has enough power behind it to make sure that you can still get some of the intense codes done that you would like. The language has a large library, works well with other coding languages if you decide to implement them together, and it is easy enough to read, even if you don’t have any kind of coding practice or experience in the past.

    In this guidebook, the examples that we are going to take a look at are going to work with Python. This is going to be helpful to ensure

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