Python Machine Learning For Beginners
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Python Machine Learning For Beginners
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Author : Finn Sanders
language : en
Publisher: Roland Bind
Release Date : 2019-05-22
Python Machine Learning For Beginners written by Finn Sanders and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-22 with Computers categories.
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!
Python Machine Learning For Beginners
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Author : Ai Publishing
language : en
Publisher:
Release Date : 2020-10-23
Python Machine Learning For Beginners written by Ai Publishing and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-23 with categories.
Python Machine Learning for BeginnersMachine Learning (ML) and Artificial Intelligence (AI) are here to stay. Yes, that's right. Based on a significant amount of data and evidence, it's obvious that ML and AI are here to stay.Consider any industry today. The practical applications of ML are really driving business results. Whether it's healthcare, e-commerce, government, transportation, social media sites, financial services, manufacturing, oil and gas, marketing and salesYou name it. The list goes on. There's no doubt that ML is going to play a decisive role in every domain in the future.But what does a Machine Learning professional do?A Machine Learning specialist develops intelligent algorithms that learn from data and also adapt to the data quickly. Then, these high-end algorithms make accurate predictions. Python Machine Learning for Beginners presents you with a hands-on approach to learn ML fast.How Is This Book Different?AI Publishing strongly believes in learning by doing methodology. With this in mind, we have crafted this book with care. You will find that the emphasis on the theoretical aspects of machine learning is equal to the emphasis on the practical aspects of the subject matter.You'll learn about data analysis and visualization in great detail in the first half of the book. Then, in the second half, you'll learn about machine learning and statistical models for data science.Each chapter presents you with the theoretical framework behind the different data science and machine learning techniques, and practical examples illustrate the working of these techniques.When you buy this book, your learning journey becomes so much easier. The reason is you get instant access to all the related learning material presented with this book--references, PDFs, Python codes, and exercises--on the publisher's website. All this material is available to you at no extra cost. You can download the ML datasets used in this book at runtime, or you can access them via the Resources/Datasets folder.You'll also find the short course on Python programming in the second chapter immensely useful, especially if you are new to Python. Since this book gives you access to all the Python codes and datasets, you only need access to a computer with the internet to get started. The topics covered include: Introduction and Environment Setup Python Crash Course Python NumPy Library for Data Analysis Introduction to Pandas Library for Data Analysis Data Visualization via Matplotlib, Seaborn, and Pandas Libraries Solving Regression Problems in ML Using Sklearn Library Solving Classification Problems in ML Using Sklearn Library Data Clustering with ML Using Sklearn Library Deep Learning with Python TensorFlow 2.0 Dimensionality Reduction with PCA and LDA Using Sklearn Click the BUY NOW button to start your Machine Learning journey.
Python Machine Learning
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Author : Andrew Park
language : en
Publisher: Andrew Park
Release Date : 2021-04-27
Python Machine Learning written by Andrew Park and has been published by Andrew Park this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-27 with categories.
★ 55% OFF for Bookstores! NOW at $ 17.99 instead of $ 39.97! LAST DAYS! ★ Do you want to learn how to design and master different Machine Learning algorithms quickly and easily?Your Customers Will Love This Amazing Guide! Today, we live in the era of Artificial Intelligence. Self-driving cars, customized product recommendations, real-time pricing, speech and facial recognition are just a few examples proving this truth. Also, think about medical diagnostics or automation of mundane and repetitive labor tasks; all these highlight the fact that we live in interesting times. From research topics to projects and applications in different stages of production, there is a lot going on in the world of Machine Learning. Machines and automation represent a huge part of our daily life. They are becoming part of our experience and existence. This is Machine Learning. Artificial Intelligence is currently one of the most thriving fields any programmer would wish to delve into, and for a good reason: this is the future! Simply put, Machine Learning is about teaching machines to think and make decisions as we would. The difference between the way machines learn and the way we do is that while for the most part we learn from experiences, machines learn from data. Starting from scratch, Python Machine Learning explains how this happens, how machines build their experience and compounding knowledge. Data forms the core of Machine Learning because within data lie truths whose depths exceed our imagination. The computations machines can perform on data are incredible, beyond anything a human brain could do. Once we introduce data to a machine learning model, we must create an environment where we update the data stream frequently. This builds the machine's learning ability. The more data Machine Learning models are exposed to, the easier it is for these models to expand their potential. Some of the topics that we will discuss inside include: What is Machine Learning and how it is applied in real-world situations Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence Supervised learning, unsupervised learning, and semi-supervised learning The place of Regression techniques in Machine Learning, including Linear Regression in Python Machine learning training models How to use Lists and Modules in Python The 12 essential libraries for Machine Learning in Python What is the Tensorflow library Artificial Neural Networks And Much More! While most books only focus on widespread details without going deeper into the different models and techniques, Python Machine Learning explains how to master the concepts of Machine Learning technology and helps you to understand how researchers are breaking the boundaries of Data Science to mimic human intelligence in machines using various Machine Learning algorithms. Even if some concepts of Machine Learning algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way. Would You Like To Know More? Buy It NOW And Let Your Customers Get Addicted To This Amazing Book!
Python Machine Learning From Scratch
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Author : Jonathan Adam
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2016-08-24
Python Machine Learning From Scratch written by Jonathan Adam and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-24 with categories.
***** BUY NOW (will soon return to 25.89 $)******Free eBook for customers who purchase the print book from Amazon****** Are you thinking of learning more about Machine Learning using Python? (For Beginners) This book would seek to explain common terms and algorithms in an intuitive way. The author used a progressive approach whereby we start out slowly and improve on the complexity of our solutions. From AI Sciences Publisher Our books may be the best one for beginners; it's a step-by-step guide for any person who wants to start learning Artificial Intelligence and Data Science from scratch. It will help you in preparing a solid foundation and learn any other high-level courses.To get the most out of the concepts that would be covered, readers are advised to adopt a hands on approach which would lead to better mental representations. Step By Step Guide and Visual Illustrations and Examples This book and the accompanying examples, you would be well suited to tackle problems which pique your interests using machine learning.Instead of tough math formulas, this book contains several graphs and images which detail all important Machine Learning concepts and their applications. Target Users The book designed for a variety of target audiences. The most suitable users would include: Anyone who is intrigued by how algorithms arrive at predictions but has no previous knowledge of the field. Software developers and engineers with a strong programming background but seeking to break into the field of machine learning. Seasoned professionals in the field of artificial intelligence and machine learning who desire a bird's eye view of current techniques and approaches. What's Inside This Book? Supervised Learning Algorithms Unsupervised Learning Algorithms Semi-supervised Learning Algorithms Reinforcement Learning Algorithms Overfitting and underfitting correctness The Bias-Variance Trade-off Feature Extraction and Selection A Regression Example: Predicting Boston Housing Prices Import Libraries: How to forecast and Predict Popular Classification Algorithms Introduction to K Nearest Neighbors Introduction to Support Vector Machine Example of Clustering Running K-means with Scikit-Learn Introduction to Deep Learning using TensorFlow Deep Learning Compared to Other Machine Learning Approaches Applications of Deep Learning How to run the Neural Network using TensorFlow Cases of Study with Real Data Sources & References Frequently Asked Questions Q: Is this book for me and do I need programming experience?A: If you want to smash Machine Learning from scratch, this book is for you. If you already wrote a few lines of code and recognize basic programming statements, you'll be OK.Q: Does this book include everything I need to become a Machine Learning expert?A: Unfortunately, no. This book is designed for readers taking their first steps in Machine Learning and further learning will be required beyond this book to master all aspects of Machine Learning.Q: Can I have a refund if this book is not fitted for me?A: Yes, Amazon refund you if you aren't satisfied, for more information about the amazon refund service please go to the amazon help platform. We will also be happy to help you if you send us an email at contact@aisciences.net.AI Sciences Company offers you a free eBooks at http://aisciences.net/free/
Python Machine Learning
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Author : Sebastian Raschka
language : en
Publisher: Packt Publishing Ltd
Release Date : 2015-09-23
Python Machine Learning written by Sebastian Raschka and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-09-23 with Computers categories.
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Python Machine Learning For Beginners 2021
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Author : Steven Williams
language : en
Publisher:
Release Date : 2020-12-05
Python Machine Learning For Beginners 2021 written by Steven Williams and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-05 with categories.
If you want to learn how to design and master different Machine Learning algorithms quickly and easily, then keep reading. We live in a world of data deluge where gigabytes of data are generated daily. It is possible that this data might not be very useful for our daily applications. Major setbacks in the use of such data may be due to the presence of loopholes in data links previously generated or the data might be too vast for the limited human mind. Machine learning in this book presents some of the solutions to the problems above. Being an introductory guide, expect to learn the various basics involved in Machine Learning and Python. This book provides an insight into the new world of big data, then behooves you to learn more about Machine Learning. With a detailed and concise overview of the fundamentals, along with the challenges and limitations currently being tackled by the pros, inside this comprehensive guide you will Learn the Fundamentals of Machine Learning which Are Being Developed and Advanced with Python What is Machine Learning and how it is applied in real-world situations Algorithms, in a Language that Requires No Prior Background in Python Discover best practices for evaluating and tuning models Discover the Details of the Supervised, Unsupervised, and Reinforcement Algorithms, which Serve as the Skeleton of Hundreds of Machine Learning Algorithms Being Developed Every Day Become Familiar with Data Science Technology, an Umbrella Term Used for the Cutting-Edge Technologies of Today Understand the Entire Process of Creating Neural Network Models on TensorFlow, Using Open Source Data Sets and real Python Code Uncover the Secrets of the Most Critical Aspect of Developing a Machine Learning Model - Data Pre-Processing and Training/Testing Subsets Artificial Neural Networks And Much More! So what are you waiting for? Even if some concepts of Machine Learning algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way. Would You Like To Know More? Scroll up and click on the BUY NOW button to get your copy now!
Python Machine Learning
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Author : Railey Brandon
language : en
Publisher: Roland Bind
Release Date : 2019-04-25
Python Machine Learning written by Railey Brandon and has been published by Roland Bind this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-25 with Computers categories.
★☆Have you come across the terms machine learning and neural networks in most articles you have recently read? Do you also want to learn how to build a machine learning model that will answer your questions within a blink of your eyes?☆★ If you responded yes to any of the above questions, you have come to the right place. Machine learning is an incredibly dense topic. It's hard to imagine condensing it into an easily readable and digestible format. However, this book aims to do exactly that. Machine learning and artificial intelligence have been used in different machines and applications to improve the user's experience. One can also use machine learning to make data analysis and predicting the output for some data sets easy. All you need to do is choose the right algorithm, train the model and test the model before you apply it on any real-world tool. It is that simple isn't it? ★★Apart from this, you will also learn more about★★ ♦ The Different Types Of Learning Algorithm That You Can Expect To Encounter ♦ The Numerous Applications Of Machine Learning And Deep Learning ♦ The Best Practices For Picking Up Neural Networks ♦ What Are The Best Languages And Libraries To Work With ♦ The Various Problems That You Can Solve With Machine Learning Algorithms ♦ And much more... Well, you can do it faster if you use Python. This language has made it easy for any user, even an amateur, to build a strong machine learning model since it has numerous directories and libraries that make it easy for one to build a model. Do you want to know how to build a machine learning model and a neural network? So, what are you waiting for? Grab a copy of this book now!
Python Machine Learning
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Author : Kevin Howey
language : en
Publisher: Kevin Howey
Release Date : 2021-03-18
Python Machine Learning written by Kevin Howey and has been published by Kevin Howey this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-18 with categories.
⭐ 55% OFF for Bookstores! NOW at $11.99 instead of $24.99! Your Customers Will Never Stop Using This Awesome Book!
Python Machine Learning
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Author : Richard Moore
language : en
Publisher:
Release Date : 2020-03-03
Python Machine Learning written by Richard Moore and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-03 with categories.
Are you looking for a guide of Machine Learning? The purpose of this book is to guide you step by step through the entire process of working with various machine learning algorithms. First you will learn the basics of working with Python in order to acquire the basic knowledge needed to understand machine learning. In each chapter you will learn a great deal of theory backed up by practical examples. Once you have the basics down, you will get to the core of Machine Learning algorithms and techniques. You will explore: Why machine learning is important and so popular with today's tech industry. The basics of working with Python. How to set up the development environment with the help of Python scientific distributions and libraries. How to preprocess your data and prepare it for training. How to work with the most important machine learning algorithms such as support vector machines and decision trees. The power of neural networks and how to work with feedforward, recurrent, and convolutional networks. Learn machine learning and working with training algorithms doesn't have to be a complex journey. Scroll up and click buy now so that Python Machine Learning can guide you step by step through the entire process.
Python Machine Learning
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Author : Brady Ellison
language : en
Publisher:
Release Date :
Python Machine Learning written by Brady Ellison and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Ready to discover the Machine Learning world? Machine learning paves the path into the future and it’s powered by Python. All industries can benefit from machine learning and artificial intelligence whether we’re talking about private businesses, healthcare, infrastructure, banking, or social media. What exactly does it do for us and what does a machine learning specialist do? Machine learning professionals create and implement special algorithms that can learn from existing data to make an accurate prediction on new never before seen data. Python Machine Learning presents you a step-by-step guide on how to create machine learning models that lead to valuable results. The book focuses on machine learning theory as much as practical examples. You will learn how to analyse data, use visualization methods, implement regression and classification models, and how to harness the power of neural networks. By purchasing this book, your machine learning journey becomes a lot easier. While a minimal level of Python programming is recommended, the algorithms and techniques are explained in such a way that you don’t need to be intimidated by mathematics. The Topics Covered Include: Machine learning fundamentals How to set up the development environment How to use Python libraries and modules like Scikit-learn, TensorFlow, Matplotlib, and NumPy How to explore data How to solve regression and classification problems Decision trees k-means clustering Feed-forward and recurrent neural networks Get your copy now