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Machine Learning Algorithms Using Python Programming


Machine Learning Algorithms Using Python Programming
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Machine Learning Algorithms Using Python Programming


Machine Learning Algorithms Using Python Programming
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Author : Gopal Sakarkar
language : en
Publisher: Nova Science Publishers
Release Date : 2021

Machine Learning Algorithms Using Python Programming written by Gopal Sakarkar and has been published by Nova Science Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with Computers categories.


"The machine learning field is concerned with the question of how to create computer programs that automatically improve information. In recent years, many successful electronic learning applications have been made, from data mining systems that learn to detect fraudulent credit card transactions, filtering programs that learn user readings, to private cars that learn to drive on public highways. At the same time, there have been significant developments in the concepts and algorithms that form the basis for this field. Machine learning is programming computers to optimize a performance criterion using example data or past experience. The goal of this textbook is to present the key concepts of Machine Learning which includes Python concepts and Interpreter, Foundation of Machine Learning, Data Pre-processing, Supervised Machine Learning, Unsupervised Machine Learning, Reinforcement Learning, Kernel Machine, Design and analysis of Machine Learning experiment and Data visualization. The theoretical concepts along with coding implementation are covered. This book aims to pursue a middle ground between a theoretical textbook and one that focuses on applications. The book concentrates on the important ideas in machine learning"--



Python Machine Learning For Beginners


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


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



Python Reinforcement Learning Projects


Python Reinforcement Learning Projects
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Author : Sean Saito
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-09-29

Python Reinforcement Learning Projects written by Sean Saito 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 2018-09-29 with Computers categories.


Implement state-of-the-art deep reinforcement learning algorithms using Python and its powerful libraries Key FeaturesImplement Q-learning and Markov models with Python and OpenAIExplore the power of TensorFlow to build self-learning modelsEight AI projects to gain confidence in building self-trained applicationsBook Description Reinforcement learning is one of the most exciting and rapidly growing fields in machine learning. This is due to the many novel algorithms developed and incredible results published in recent years. In this book, you will learn about the core concepts of RL including Q-learning, policy gradients, Monte Carlo processes, and several deep reinforcement learning algorithms. As you make your way through the book, you'll work on projects with datasets of various modalities including image, text, and video. You will gain experience in several domains, including gaming, image processing, and physical simulations. You'll explore technologies such as TensorFlow and OpenAI Gym to implement deep learning reinforcement learning algorithms that also predict stock prices, generate natural language, and even build other neural networks. By the end of this book, you will have hands-on experience with eight reinforcement learning projects, each addressing different topics and/or algorithms. We hope these practical exercises will provide you with better intuition and insight about the field of reinforcement learning and how to apply its algorithms to various problems in real life. What you will learnTrain and evaluate neural networks built using TensorFlow for RLUse RL algorithms in Python and TensorFlow to solve CartPole balancingCreate deep reinforcement learning algorithms to play Atari gamesDeploy RL algorithms using OpenAI UniverseDevelop an agent to chat with humans Implement basic actor-critic algorithms for continuous controlApply advanced deep RL algorithms to games such as MinecraftAutogenerate an image classifier using RLWho this book is for Python Reinforcement Learning Projects is for data analysts, data scientists, and machine learning professionals, who have working knowledge of machine learning techniques and are looking to build better performing, automated, and optimized deep learning models. Individuals who want to work on self-learning model projects will also find this book useful.



Machine Learning


Machine Learning
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Author : Samuel Hack
language : en
Publisher:
Release Date : 2021-01-07

Machine Learning written by Samuel Hack and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-07 with Computers categories.


Master the world of Python and Machine Learning with this incredible 4-in-1 bundle. Are you interested in becoming a Python pro?Do you want to learn more about the incredible world of machine learning, and what it can do for you? Then keep reading. Created with the beginner in mind, this powerful bundle delves into the fundamentals behind Python and Machine Learning, from basic code and mathematical formulas to complex neural networks and ensemble modeling. Inside, you'll discover everything you need to know to get started with Python and Machine Learning, and begin your journey to success! In book one - MACHINE LEARNING FOR BEGINNERS, you'll learn: What is Artificial Intelligence Really, and Why is it So Powerful? Choosing the Right Kind of Machine Learning Model for You An Introduction to Statistics Reinforcement Learning and Ensemble Modeling "Random Forests" and Decision Trees In book two - MACHINE LEARNING MATHEMATICS, you will: Learn the Fundamental Concepts of Machine Learning Algorithms Understand The Four Fundamental Types of Machine Learning Algorithm Master the Concept of "Statistical Learning" Learn Everything You Need to Know about Neural Networks and Data Pipelines Master the Concept of "General Setting of Learning" In book three - LEARNING PYTHON, you'll discover: How to Install, Run, and Understand Python on Any Operating System A Comprehensive Introduction to Python Python Basics and Writing Code Writing Loops, Conditional Statements, Exceptions and More Python Expressions and The Beauty of Inheritances And in book four - PYTHON MACHINE LEARNING, you will: Learn the Fundamentals of Machine Learning Master the Nuances of 12 of the Most Popular and Widely-Used Machine Learning Algorithms Become Familiar with Data Science Technology Dive Into the Functioning of Scikit-Learn Library and Develop Machine Learning Models Uncover the Secrets of the Most Critical Aspect of Developing a Machine Learning Model - Data Pre-Processing and Training/Testing Subsets Whether you're a complete beginner or a programmer looking to improve your skillset, this bundle is your all-in-one solution to mastering the world of Python and Machine Learning. So don't wait - it's never been easier to learn. Buy Now to Become a Master of Python and Machine Learning Today!



Machine Learning With Python


Machine Learning With Python
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Author : Matt Algore
language : en
Publisher:
Release Date : 2021-01-07

Machine Learning With Python written by Matt Algore and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-07 with categories.




Python Machine Learning By Example


Python Machine Learning By Example
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Author : Yuxi (Hayden) Liu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-10-30

Python Machine Learning By Example written by Yuxi (Hayden) Liu 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 2020-10-30 with Computers categories.


A comprehensive guide to get you up to speed with the latest developments of practical machine learning with Python and upgrade your understanding of machine learning (ML) algorithms and techniques Key FeaturesDive into machine learning algorithms to solve the complex challenges faced by data scientists todayExplore cutting edge content reflecting deep learning and reinforcement learning developmentsUse updated Python libraries such as TensorFlow, PyTorch, and scikit-learn to track machine learning projects end-to-endBook Description Python Machine Learning By Example, Third Edition serves as a comprehensive gateway into the world of machine learning (ML). With six new chapters, on topics including movie recommendation engine development with Naïve Bayes, recognizing faces with support vector machine, predicting stock prices with artificial neural networks, categorizing images of clothing with convolutional neural networks, predicting with sequences using recurring neural networks, and leveraging reinforcement learning for making decisions, the book has been considerably updated for the latest enterprise requirements. At the same time, this book provides actionable insights on the key fundamentals of ML with Python programming. Hayden applies his expertise to demonstrate implementations of algorithms in Python, both from scratch and with libraries. Each chapter walks through an industry-adopted application. With the help of realistic examples, you will gain an understanding of the mechanics of ML techniques in areas such as exploratory data analysis, feature engineering, classification, regression, clustering, and NLP. By the end of this ML Python book, you will have gained a broad picture of the ML ecosystem and will be well-versed in the best practices of applying ML techniques to solve problems. What you will learnUnderstand the important concepts in ML and data scienceUse Python to explore the world of data mining and analyticsScale up model training using varied data complexities with Apache SparkDelve deep into text analysis and NLP using Python libraries such NLTK and GensimSelect and build an ML model and evaluate and optimize its performanceImplement ML algorithms from scratch in Python, TensorFlow 2, PyTorch, and scikit-learnWho this book is for If you’re a machine learning enthusiast, data analyst, or data engineer highly passionate about machine learning and want to begin working on machine learning assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial, although this is not necessary.



Python Machine Learning


Python Machine Learning
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Author : Wei-Meng Lee
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-04

Python Machine Learning written by Wei-Meng Lee and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-04 with Computers categories.


Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs decreasing at the same time, there is no better time to learn machine learning using Python. Machine learning tasks that once required enormous processing power are now possible on desktop machines. However, machine learning is not for the faint of heart—it requires a good foundation in statistics, as well as programming knowledge. Python Machine Learning will help coders of all levels master one of the most in-demand programming skillsets in use today. Readers will get started by following fundamental topics such as an introduction to Machine Learning and Data Science. For each learning algorithm, readers will use a real-life scenario to show how Python is used to solve the problem at hand. • Python data science—manipulating data and data visualization • Data cleansing • Understanding Machine learning algorithms • Supervised learning algorithms • Unsupervised learning algorithms • Deploying machine learning models Python Machine Learning is essential reading for students, developers, or anyone with a keen interest in taking their coding skills to the next level.



40 Algorithms Every Programmer Should Know


40 Algorithms Every Programmer Should Know
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Author : Imran Ahmad
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-06-12

40 Algorithms Every Programmer Should Know written by Imran Ahmad 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 2020-06-12 with Computers categories.


Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental algorithms, such as sorting and searching, to modern algorithms used in machine learning and cryptography Key Features Learn the techniques you need to know to design algorithms for solving complex problems Become familiar with neural networks and deep learning techniques Explore different types of algorithms and choose the right data structures for their optimal implementation Book DescriptionAlgorithms have always played an important role in both the science and practice of computing. Beyond traditional computing, the ability to use algorithms to solve real-world problems is an important skill that any developer or programmer must have. This book will help you not only to develop the skills to select and use an algorithm to solve real-world problems but also to understand how it works. You’ll start with an introduction to algorithms and discover various algorithm design techniques, before exploring how to implement different types of algorithms, such as searching and sorting, with the help of practical examples. As you advance to a more complex set of algorithms, you'll learn about linear programming, page ranking, and graphs, and even work with machine learning algorithms, understanding the math and logic behind them. Further on, case studies such as weather prediction, tweet clustering, and movie recommendation engines will show you how to apply these algorithms optimally. Finally, you’ll become well versed in techniques that enable parallel processing, giving you the ability to use these algorithms for compute-intensive tasks. By the end of this book, you'll have become adept at solving real-world computational problems by using a wide range of algorithms.What you will learn Explore existing data structures and algorithms found in Python libraries Implement graph algorithms for fraud detection using network analysis Work with machine learning algorithms to cluster similar tweets and process Twitter data in real time Predict the weather using supervised learning algorithms Use neural networks for object detection Create a recommendation engine that suggests relevant movies to subscribers Implement foolproof security using symmetric and asymmetric encryption on Google Cloud Platform (GCP) Who this book is for This book is for programmers or developers who want to understand the use of algorithms for problem-solving and writing efficient code. Whether you are a beginner looking to learn the most commonly used algorithms in a clear and concise way or an experienced programmer looking to explore cutting-edge algorithms in data science, machine learning, and cryptography, you'll find this book useful. Although Python programming experience is a must, knowledge of data science will be helpful but not necessary.



Python Machine Learning


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!