Python Machine Learning Essentials

Author : Anurag Bhardwaj,Wei Di,Jianing Wei
Publisher : Packt Publishing Ltd
Page : 271 pages
File Size : 41,8 Mb
Release : 2018-01-30
Category : Computers
ISBN : 9781785887772

Get Book

Deep Learning Essentials by Anurag Bhardwaj,Wei Di,Jianing Wei Pdf

Get to grips with the essentials of deep learning by leveraging the power of Python Key Features Your one-stop solution to get started with the essentials of deep learning and neural network modeling Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner Book Description Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more. This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications. What you will learn Get to grips with the core concepts of deep learning and neural networks Set up deep learning library such as TensorFlow Fine-tune your deep learning models for NLP and Computer Vision applications Unify different information sources, such as images, text, and speech through deep learning Optimize and fine-tune your deep learning models for better performance Train a deep reinforcement learning model that plays a game better than humans Learn how to make your models get the best out of your GPU or CPU Who this book is for Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python.

Author : Bernard Baah
Publisher : Independently Published
Page : 0 pages
File Size : 54,9 Mb
Release : 2024-03-22
Category : Computers
ISBN : 9798884780767

Get Book

Python Machine Learning Essentials by Bernard Baah Pdf

"Python Machine Learning Essentials" by Bernard Baah is your ultimate guide to mastering machine learning concepts and techniques using Python. Whether you're a beginner or an experienced programmer, this book equips you with the knowledge and skills needed to understand and apply machine learning algorithms effectively. With a comprehensive approach, Bernard Baah takes you through the fundamentals of machine learning, covering Python basics, data preprocessing, exploratory data analysis, supervised and unsupervised learning, neural networks, natural language processing, model deployment, and more. Each chapter is filled with practical examples, code snippets, and hands-on exercises to reinforce your learning and deepen your understanding. As the founder of Filly Coder (https: //fillycoder.com), Bernard Baah brings years of experience in machine learning and software development to this book. His expertise and passion for teaching shine through, making complex concepts accessible and understandable for readers of all levels. Whether you're a data scientist, developer, or aspiring AI enthusiast, "Python Machine Learning Essentials" is your go-to resource for mastering machine learning with Python. Dive into the world of machine learning and unlock the potential to build intelligent applications with confidence. Get your copy of "Python Machine Learning Essentials" today and embark on your journey to becoming a proficient machine learning practitioner

Author : Samuel Hack
Publisher : Samuel Hack
Page : 638 pages
File Size : 54,8 Mb
Release : 2021-05-24
Category : Electronic
ISBN : 1801728771

Get Book

Machine Learning by Samuel Hack Pdf

TODAY ONLY 55% OFF for Bookstores! 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!

Author : David Paper
Publisher : Apress
Page : 247 pages
File Size : 44,5 Mb
Release : 2019-11-16
Category : Computers
ISBN : 9781484253731

Get Book

Hands-on Scikit-Learn for Machine Learning Applications by David Paper Pdf

Aspiring data science professionals can learn the Scikit-Learn library along with the fundamentals of machine learning with this book. The book combines the Anaconda Python distribution with the popular Scikit-Learn library to demonstrate a wide range of supervised and unsupervised machine learning algorithms. Care is taken to walk you through the principles of machine learning through clear examples written in Python that you can try out and experiment with at home on your own machine. All applied math and programming skills required to master the content are covered in this book. In-depth knowledge of object-oriented programming is not required as working and complete examples are provided and explained. Coding examples are in-depth and complex when necessary. They are also concise, accurate, and complete, and complement the machine learning concepts introduced. Working the examples helps to build the skills necessary to understand and apply complex machine learning algorithms. Hands-on Scikit-Learn for Machine Learning Applications is an excellent starting point for those pursuing a career in machine learning. Students of this book will learn the fundamentals that are a prerequisite to competency. Readers will be exposed to the Anaconda distribution of Python that is designed specifically for data science professionals, and will build skills in the popular Scikit-Learn library that underlies many machine learning applications in the world of Python. What You'll LearnWork with simple and complex datasets common to Scikit-Learn Manipulate data into vectors and matrices for algorithmic processing Become familiar with the Anaconda distribution used in data scienceApply machine learning with Classifiers, Regressors, and Dimensionality Reduction Tune algorithms and find the best algorithms for each dataset Load data from and save to CSV, JSON, Numpy, and Pandas formats Who This Book Is For The aspiring data scientist yearning to break into machine learning through mastering the underlying fundamentals that are sometimes skipped over in the rush to be productive. Some knowledge of object-oriented programming and very basic applied linear algebra will make learning easier, although anyone can benefit from this book.

Author : Michael Bowles
Publisher : John Wiley & Sons
Page : 361 pages
File Size : 47,9 Mb
Release : 2015-04-27
Category : Computers
ISBN : 9781118961742

Get Book

Machine Learning in Python by Michael Bowles Pdf

Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, data preparation, and using the trained models in practice. You will learn a core set of Python programming techniques, various methods of building predictive models, and how to measure the performance of each model to ensure that the right one is used. The chapters on penalized linear regression and ensemble methods dive deep into each of the algorithms, and you can use the sample code in the book to develop your own data analysis solutions. Machine learning algorithms are at the core of data analytics and visualization. In the past, these methods required a deep background in math and statistics, often in combination with the specialized R programming language. This book demonstrates how machine learning can be implemented using the more widely used and accessible Python programming language. Predict outcomes using linear and ensemble algorithm families Build predictive models that solve a range of simple and complex problems Apply core machine learning algorithms using Python Use sample code directly to build custom solutions Machine learning doesn't have to be complex and highly specialized. Python makes this technology more accessible to a much wider audience, using methods that are simpler, effective, and well tested. Machine Learning in Python shows you how to do this, without requiring an extensive background in math or statistics.

Author : Abhishek Singh
Publisher : Independently Published
Page : 0 pages
File Size : 40,7 Mb
Release : 2023-07-14
Category : Electronic
ISBN : 9798852254672

Get Book

Essential Python for Machine Learning by Abhishek Singh Pdf

"Essential Python for Machine Learning" is a comprehensive guide that equips readers with the fundamental Python programming skills necessary to kickstart their journey into the exciting world of machine learning. This book covers the essential topics and techniques required to understand and apply Python in the field of machine learning. Starting with the basics of Python programming, readers learn about conditional statements, loops, data structures, and functions. The book then delves into important libraries like NumPy and Pandas, enabling readers to manipulate and analyze data efficiently. With a focus on practical application, readers explore topics such as file handling, regular expressions, and error handling, gaining essential skills for real-world machine learning projects. Key Features: Comprehensive coverage of Python programming fundamentals. In-depth exploration of key libraries like NumPy and Pandas for data manipulation and analysis. Practical application of Python concepts to real-world machine learning scenarios. Clear explanations, illustrative examples, and practical exercises to enhance learning. Suitable for beginners and those with some programming experience looking to enter the field of machine learning. Whether you are a student, aspiring data scientist, or a Python enthusiast looking to venture into machine learning, "Essential Python for Machine Learning" provides the essential knowledge and skills needed to get started. Gain a strong foundation in Python programming and unlock the power of machine learning with this practical and accessible guide. Don't miss out on this invaluable resource for mastering Python and embarking on your machine learning journey. Get your copy of "Essential Python for Machine Learning" today and unlock the world of possibilities in data science and AI.

Author : Euan Russano,Elaine Ferreira Avelino
Publisher : Arcler Press
Page : 290 pages
File Size : 54,7 Mb
Release : 2019-11
Category : Computers
ISBN : 177407365X

Get Book

Fundamentals of Machine Learning Using Python by Euan Russano,Elaine Ferreira Avelino Pdf

Fundamentals of Machine Learning discusses the basics of python, use of python in computing and provides a general outlook on machine learning. This book provides an insight into concepts such as linear regression with one variable, linear algebra, and linear regression with multiple inputs. The classification with logistics regression model, regularization, neural networks, decision trees are explained in this book. The introduction to several concepts of machine learning such as component analysis, classification using k-Nearest Algorithm, k Means Clustering, computing with Tensor flow and natural language processing have been explained. This book explains the fundamental concepts of machine learning.

Author : Alboukadel Kassambara
Publisher : STHDA
Page : 209 pages
File Size : 52,8 Mb
Release : 2018-03-10
Category : Electronic
ISBN : 9781986406857

Get Book

Machine Learning Essentials by Alboukadel Kassambara Pdf

Discovering knowledge from big multivariate data, recorded every days, requires specialized machine learning techniques. This book presents an easy to use practical guide in R to compute the most popular machine learning methods for exploring real word data sets, as well as, for building predictive models. The main parts of the book include: A) Unsupervised learning methods, to explore and discover knowledge from a large multivariate data set using clustering and principal component methods. You will learn hierarchical clustering, k-means, principal component analysis and correspondence analysis methods. B) Regression analysis, to predict a quantitative outcome value using linear regression and non-linear regression strategies. C) Classification techniques, to predict a qualitative outcome value using logistic regression, discriminant analysis, naive bayes classifier and support vector machines. D) Advanced machine learning methods, to build robust regression and classification models using k-nearest neighbors methods, decision tree models, ensemble methods (bagging, random forest and boosting). E) Model selection methods, to select automatically the best combination of predictor variables for building an optimal predictive model. These include, best subsets selection methods, stepwise regression and penalized regression (ridge, lasso and elastic net regression models). We also present principal component-based regression methods, which are useful when the data contain multiple correlated predictor variables. F) Model validation and evaluation techniques for measuring the performance of a predictive model. G) Model diagnostics for detecting and fixing a potential problems in a predictive model. The book presents the basic principles of these tasks and provide many examples in R. This book offers solid guidance in data mining for students and researchers. Key features: - Covers machine learning algorithm and implementation - Key mathematical concepts are presented - Short, self-contained chapters with practical examples.

Author : Sebastian Raschka
Publisher : Packt Publishing Ltd
Page : 455 pages
File Size : 55,5 Mb
Release : 2015-09-23
Category : Computers
ISBN : 9781783555147

Get Book

Python Machine Learning by Sebastian Raschka Pdf

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.

Author : Anthony Mauro
Publisher : Unknown
Page : 0 pages
File Size : 50,7 Mb
Release : 2024-07-12
Category : Computers
ISBN : 9798350960624

Get Book

Python and Math Essentials for Machine Learning by Anthony Mauro Pdf

Author : Jake VanderPlas
Publisher : "O'Reilly Media, Inc."
Page : 743 pages
File Size : 40,8 Mb
Release : 2016-11-21
Category : Computers
ISBN : 9781491912133

Get Book

Python Data Science Handbook by Jake VanderPlas Pdf

For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms

Author : Patrick J
Publisher : GitforGits
Page : 260 pages
File Size : 50,8 Mb
Release : 2024-01-03
Category : Computers
ISBN : 9788119177639

Get Book

Python AI Programming by Patrick J Pdf

This book aspires young graduates and programmers to become AI engineers and enter the world of artificial intelligence by combining powerful Python programming with artificial intelligence. Beginning with the fundamentals of Python programming, the book gradually progresses to machine learning, where readers learn to implement Python in developing predictive models. The book provides a clear and accessible explanation of machine learning, incorporating practical examples and exercises that strengthen understanding. We go deep into deep learning, another vital component of AI. Readers gain a thorough understanding of how Python's frameworks and libraries can be used to create sophisticated neural networks and algorithms, which are required for tasks such as image and speech recognition. Natural Language Processing is also covered in the book, with fundamental concepts and techniques for interpreting and generating human-like language covered. The book's focus on computer vision and reinforcement learning is distinctive, presenting these cutting-edge AI fields in an approachable manner. Readers will learn how to use Python's intuitive programming paradigm to create systems that interpret visual data and make intelligent decisions based on environmental interactions. The book focuses on ethical AI development and responsible programming, emphasizing the importance of developing AI that is fair, transparent, and accountable. Each chapter is designed to improve learning by including practical examples, case studies, and exercises that provide hands-on experience. This book is an excellent starting point for anyone interested in becoming an AI engineer, providing the necessary foundational knowledge and skills to delve into the fascinating world of artificial intelligence. Key Learnings Explore Python basics and AI integration for real-world application and career advancement. Experience the power of Python in AI with practical machine learning techniques. Practice Python's deep learning tools for innovative AI solution development. Dive into NLP with Python to revolutionize data interpretation and communication strategies. Simple yet practical understanding of reinforcement learning for strategic AI decision making. Uncover ethical AI development and frameworks, and concepts of responsible and trustworthy AI. Harness Python's capabilities for creating AI applications with a focus on fairness and bias. Table of Content Introduction to Artificial Intelligence Python for AI Data as Fuel for AI Machine Learning Foundation Essentials of Deep Learning NLP and Computer Vision Hands-on Reinforcement Learning Ethics to AI

Author : Francois Chollet
Publisher : Simon and Schuster
Page : 597 pages
File Size : 47,5 Mb
Release : 2017-11-30
Category : Computers
ISBN : 9781638352044

Get Book

Deep Learning with Python by Francois Chollet Pdf

Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

Author : Alex Campbell
Publisher : Unknown
Page : 110 pages
File Size : 51,7 Mb
Release : 2020-06-30
Category : Electronic
ISBN : 9798661240071

Get Book

Python Machine Learning by Alex Campbell Pdf

Machine learning is fast becoming an important technique used by multiple industries, and in applications and research. But you don't have to be part of a massive organization with an endless pot of money to get involved. Even beginners using the Python programming language can be a part of machine learning, and that is what this book is for. Today, the only limit to machine learning is your imagination. In this book, I provide you with an overview of machine learning and some practical work to get your hands dirty. Here's what you will learn: Important machine learning concepts and applications The difference between supervised and unsupervised learning Commonly used supervised and unsupervised learning algorithms and models What libraries you will benefit from using How to visualize your data Regression and classification learning models An introduction to data science The five-step plan to becoming a data scientist Ten things that everyone needs to know about machine learning You'll even get a complete hands-on project that takes you through building your own machine learning project. What you won't get is a lesson on using Python programming language; this book requires that you already know the basics. So, if you are interested in taking your programming even further, scroll up, hit that Buy Now button, and start a new journey of discovery.

Author : Samuel Hack
Publisher : Unknown
Page : 214 pages
File Size : 49,6 Mb
Release : 2021-01-08
Category : Computers
ISBN : 1801146640

Get Book

Python Machine Learning by Samuel Hack Pdf