Hands-On Markov Models with Python
Hidden Markov Model (HMM) is a statistical model based on the Markov chain concept. Hands-On Markov Models with Python helps you get to grips with HMMs and different inference algorithms by working on real-world problems. The hands-on examples explored in the book help you simplify the process flow in machine learning by using Markov model concepts, thereby making it accessible to everyone. Once you've covered the basic concepts of Markov chains, you'll get insights into Markov processes, models, and types with the help of practical examples. After grasping these fundamentals, you'll move on to learning about the different algorithms used in inferences and applying them in state and parameter inference. In addition to this, you'll explore the Bayesian approach of inference and learn how to apply it in HMMs. In further chapters, you'll discover how to use HMMs in time series analysis and natural language processing (NLP) using Python. You'll also learn to apply HMM to image proces ...
Hidden Markov Model (HMM) is a statistical model based on the Markov chain concept. Hands-On Markov Models with Python helps you get to grips with HMMs and different inference algorithms by working on real-world problems. The hands-on examples explored in the book help you simplify the process flow in machine learning by using Markov model concepts, thereby making it accessible to everyone. Once you've covered the basic concepts of Markov chains, you'll get insights into Markov processes, models, and types with the help of practical examples. After grasping these fundamentals, you'll move on to learning about the different algorithms used in inferences and applying them in state and parameter inference. In addition to this, you'll explore the Bayesian approach of inference and learn how to apply it in HMMs. In further chapters, you'll discover how to use HMMs in time series analysis and natural language processing (NLP) using Python. You'll also learn to apply HMM to image proces ...
Mastering Exploratory Analysis with pandas
The pandas is a Python library that lets you manipulate, transform, and analyze data. It is a popular framework for exploratory data visualization and analyzing datasets and data pipelines based on their properties. This book will be your practical guide to exploring datasets using pandas. You will start by setting up Python, pandas, and Jupyter Notebooks. You will learn how to use Jupyter Notebooks to run Python code. We then show you how to get data into pandas and do some exploratory analysis, before learning how to manipulate and reshape data using pandas methods. You will also learn how to deal with missing data from your datasets, how to draw charts and plots using pandas and Matplotlib, and how to create some effective visualizations for your audience. Finally, you will wrapup your newly gained pandas knowledge by learning how to import data out of pandas into some popular file formats. By the end of this book, you will have a better understanding of exploratory analysis a ...
The pandas is a Python library that lets you manipulate, transform, and analyze data. It is a popular framework for exploratory data visualization and analyzing datasets and data pipelines based on their properties. This book will be your practical guide to exploring datasets using pandas. You will start by setting up Python, pandas, and Jupyter Notebooks. You will learn how to use Jupyter Notebooks to run Python code. We then show you how to get data into pandas and do some exploratory analysis, before learning how to manipulate and reshape data using pandas methods. You will also learn how to deal with missing data from your datasets, how to draw charts and plots using pandas and Matplotlib, and how to create some effective visualizations for your audience. Finally, you will wrapup your newly gained pandas knowledge by learning how to import data out of pandas into some popular file formats. By the end of this book, you will have a better understanding of exploratory analysis a ...
Hands-On Data Structures and Algorithms with Python, 2nd Edition
Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithm ...
Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithm ...
Hands-On GPU Programming with Python and CUDA
Hands-On GPU Programming with Python and CUDA hits the ground running: you'll start by learning how to apply Amdahl's Law, use a code profiler to identify bottlenecks in your Python code, and set up an appropriate GPU programming environment. You'll then see how to "query" the GPU's features and copy arrays of data to and from the GPU's own memory. As you make your way through the book, you'll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You'll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you'll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS. With a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You'll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you'll see some topics and ...
Hands-On GPU Programming with Python and CUDA hits the ground running: you'll start by learning how to apply Amdahl's Law, use a code profiler to identify bottlenecks in your Python code, and set up an appropriate GPU programming environment. You'll then see how to "query" the GPU's features and copy arrays of data to and from the GPU's own memory. As you make your way through the book, you'll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You'll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you'll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS. With a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You'll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you'll see some topics and ...
Python Machine Learning, 3rd Edition
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, ...
Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, ...
Mastering Large Datasets with Python
Modern data science solutions need to be clean, easy to read, and scalable. In Mastering Large Datasets with Python, author J.T. Wolohan teaches you how to take a small project and scale it up using a functionally influenced approach to Python coding. You'll explore methods and built-in Python tools that lend themselves to clarity and scalability, like the high-performing parallelism method, as well as distributed technologies that allow for high data throughput. The abundant hands-on exercises in this practical tutorial will lock in these essential skills for any large-scale data science project. Programming techniques that work well on laptop-sized data can slow to a crawl - or fail altogether - when applied to massive files or distributed datasets. By mastering the powerful map and reduce paradigm, along with the Python-based tools that support it, you can write data-centric applications that scale efficiently without requiring codebase rewrites as your requirements change. Ma ...
Modern data science solutions need to be clean, easy to read, and scalable. In Mastering Large Datasets with Python, author J.T. Wolohan teaches you how to take a small project and scale it up using a functionally influenced approach to Python coding. You'll explore methods and built-in Python tools that lend themselves to clarity and scalability, like the high-performing parallelism method, as well as distributed technologies that allow for high data throughput. The abundant hands-on exercises in this practical tutorial will lock in these essential skills for any large-scale data science project. Programming techniques that work well on laptop-sized data can slow to a crawl - or fail altogether - when applied to massive files or distributed datasets. By mastering the powerful map and reduce paradigm, along with the Python-based tools that support it, you can write data-centric applications that scale efficiently without requiring codebase rewrites as your requirements change. Ma ...
Making Games with Python & Pygame
Making Games with Python & Pygame covers the Pygame library with the source code for 11 games. Making Games was written as a sequel for the same age range as Invent with Python. Once you have an understanding of the basics of Python programming, you can now expand your abilities using the Pygame library to make games with graphics, animation, and sound. This book features seven different games that are clones of popular games that you've probably already played. The games are a lot more fun and interactive than the text-based games in Invent with Python, but are still fairly short. All of the programs are less than 600 lines long. This is pretty small when you consider that professional games you download or buy in a store can be hundreds of thousands of lines long. These games require an entire team of programmers and artists working with each other for months or years to make. The book features the source code to 11 games. The games are clones of classics such as Nibbles, Tetri ...
Making Games with Python & Pygame covers the Pygame library with the source code for 11 games. Making Games was written as a sequel for the same age range as Invent with Python. Once you have an understanding of the basics of Python programming, you can now expand your abilities using the Pygame library to make games with graphics, animation, and sound. This book features seven different games that are clones of popular games that you've probably already played. The games are a lot more fun and interactive than the text-based games in Invent with Python, but are still fairly short. All of the programs are less than 600 lines long. This is pretty small when you consider that professional games you download or buy in a store can be hundreds of thousands of lines long. These games require an entire team of programmers and artists working with each other for months or years to make. The book features the source code to 11 games. The games are clones of classics such as Nibbles, Tetri ...
Invent Your Own Computer Games with Python
Invent Your Own Computer Games with Python teaches you how to program in the Python language. Each chapter gives you the complete source code for a new game, and then teaches the programming concepts from the examples. Games include Guess the Number, Hangman, Tic Tac Toe, and Reversi. This book also has an introduction to making games with 2D graphics using the Pygame framework. Programming isn't hard. But it is hard to find learning materials that teach you to do interesting things with programming. Other computer books go over many topics most newbie coders don't need. This book will teach you how to program your own computer games. You'll learn a useful skill and have fun games to show for it! ...
Invent Your Own Computer Games with Python teaches you how to program in the Python language. Each chapter gives you the complete source code for a new game, and then teaches the programming concepts from the examples. Games include Guess the Number, Hangman, Tic Tac Toe, and Reversi. This book also has an introduction to making games with 2D graphics using the Pygame framework. Programming isn't hard. But it is hard to find learning materials that teach you to do interesting things with programming. Other computer books go over many topics most newbie coders don't need. This book will teach you how to program your own computer games. You'll learn a useful skill and have fun games to show for it! ...
Deep Learning with Python
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This new edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group. You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning mod ...
Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory and practice. This new edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and practical know-how with PyTorch, a platform developed by Facebook's Artificial Intelligence Research Group. You'll start with a perspective on how and why deep learning with PyTorch has emerged as an path-breaking framework with a set of tools and techniques to solve real-world problems. Next, the book will ground you with the mathematical fundamentals of linear algebra, vector calculus, probability and optimization. Having established this foundation, you'll move on to key components and functionality of PyTorch including layers, loss functions and optimization algorithms. You'll also gain an understanding of Graphical Processing Unit (GPU) based computation, which is essential for training deep learning mod ...
Building Versatile Mobile Apps with Python and REST
Develop versatile iOS apps using Python with RESTful web services. This book will show you how to blend Django, a high-level Python Web framework, with Django REST, the powerful, feature-filled extension, to build iOS mobile apps. Using easy-to-follow examples, you'll begin by building a simple app using the RESTful Web API and iOS. You'll begin by using traditional Django to create models and connect your App to the database. You'll then see how to serialize your data and create the RESTful API. The second part of the book introduces Xcode, a programming environment to develop iOS apps. Using Swift, the programming language for iOS, you'll design the actual app. Once you have your back-end in Django and a front-end in Swift, you'll connect them using our RESTful API. You'll be able to log in, browse places of interest, and rate them and leave comments. Guided step-by-step instructions, Building Versatile Mobile Apps with Python and REST will demonstrate how easy it is to use Py ...
Develop versatile iOS apps using Python with RESTful web services. This book will show you how to blend Django, a high-level Python Web framework, with Django REST, the powerful, feature-filled extension, to build iOS mobile apps. Using easy-to-follow examples, you'll begin by building a simple app using the RESTful Web API and iOS. You'll begin by using traditional Django to create models and connect your App to the database. You'll then see how to serialize your data and create the RESTful API. The second part of the book introduces Xcode, a programming environment to develop iOS apps. Using Swift, the programming language for iOS, you'll design the actual app. Once you have your back-end in Django and a front-end in Swift, you'll connect them using our RESTful API. You'll be able to log in, browse places of interest, and rate them and leave comments. Guided step-by-step instructions, Building Versatile Mobile Apps with Python and REST will demonstrate how easy it is to use Py ...