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Author: Brian Luff Publisher: Lulu.com ISBN: 1447860985 Category : Humor Languages : en Pages : 295
Book Description
Special edition of this popular paperback with bonus photo section and a brand new final chapter which brings the story up to date. When scriptwriters Georgina Sowerby and Brian Luff began recording podcasts in their spare bedroom in 2005, they had no way of knowing what an adventure they were embarking upon. Sex Tips for Pandas is the story of a couple from London whose podcasts touched the hearts of thousands and propelled them on a bizarre and comical trip around the world. It's also an intimate, often confessional book about a relationship, and a tantalizing glimpse at the none-too-glamorous side of the entertainment industry. For Brian and Georgina podcasting was an obsessive shared interest, a form of escapism from the real world which became the very glue that held their often difficult and complicated relationship together. Sprinkled throughout with showbiz anecdotes and bitchy behind-the-scenes gossip, Sex Tips For Pandas will amuse you, entertain you and ultimately inspire you.
Author: Brian Luff Publisher: Lulu.com ISBN: 1447860985 Category : Humor Languages : en Pages : 295
Book Description
Special edition of this popular paperback with bonus photo section and a brand new final chapter which brings the story up to date. When scriptwriters Georgina Sowerby and Brian Luff began recording podcasts in their spare bedroom in 2005, they had no way of knowing what an adventure they were embarking upon. Sex Tips for Pandas is the story of a couple from London whose podcasts touched the hearts of thousands and propelled them on a bizarre and comical trip around the world. It's also an intimate, often confessional book about a relationship, and a tantalizing glimpse at the none-too-glamorous side of the entertainment industry. For Brian and Georgina podcasting was an obsessive shared interest, a form of escapism from the real world which became the very glue that held their often difficult and complicated relationship together. Sprinkled throughout with showbiz anecdotes and bitchy behind-the-scenes gossip, Sex Tips For Pandas will amuse you, entertain you and ultimately inspire you.
Author: Daniel Y. Chen Publisher: Addison-Wesley Professional ISBN: 0134547055 Category : Computers Languages : en Pages : 1093
Book Description
The Hands-On, Example-Rich Introduction to Pandas Data Analysis in Python Today, analysts must manage data characterized by extraordinary variety, velocity, and volume. Using the open source Pandas library, you can use Python to rapidly automate and perform virtually any data analysis task, no matter how large or complex. Pandas can help you ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. Pandas for Everyone brings together practical knowledge and insight for solving real problems with Pandas, even if you’re new to Python data analysis. Daniel Y. Chen introduces key concepts through simple but practical examples, incrementally building on them to solve more difficult, real-world problems. Chen gives you a jumpstart on using Pandas with a realistic dataset and covers combining datasets, handling missing data, and structuring datasets for easier analysis and visualization. He demonstrates powerful data cleaning techniques, from basic string manipulation to applying functions simultaneously across dataframes. Once your data is ready, Chen guides you through fitting models for prediction, clustering, inference, and exploration. He provides tips on performance and scalability, and introduces you to the wider Python data analysis ecosystem. Work with DataFrames and Series, and import or export data Create plots with matplotlib, seaborn, and pandas Combine datasets and handle missing data Reshape, tidy, and clean datasets so they’re easier to work with Convert data types and manipulate text strings Apply functions to scale data manipulations Aggregate, transform, and filter large datasets with groupby Leverage Pandas’ advanced date and time capabilities Fit linear models using statsmodels and scikit-learn libraries Use generalized linear modeling to fit models with different response variables Compare multiple models to select the “best” Regularize to overcome overfitting and improve performance Use clustering in unsupervised machine learning
Author: Shekhar Khandelwal Publisher: BPB Publications ISBN: 9355515391 Category : Computers Languages : en Pages : 251
Book Description
A hands-on guide to building and deploying deep learning models with Python KEY FEATURES ● Acquire the skills to perform exploratory data analysis, uncover insights, and preprocess data for deep learning tasks. ● Build and train various types of neural networks, including Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs). ● Gain hands-on experience by working on practical projects and applying deep learning techniques to real-world problems. DESCRIPTION “Deep Learning for Data Architects” is a comprehensive guide that bridges the gap between data architecture and deep learning. It provides a solid foundation in Python for data science and serves as a launchpad into the world of AI and deep learning. The book begins by addressing the challenges of transforming raw data into actionable insights. It provides a practical understanding of data handling and covers the construction of neural network-based predictive models. The book then explores specialized networks such as convolutional neural networks (CNNs), recurrent neural networks (RNNs), and generative adversarial networks (GANs). The book delves into the theory and practical aspects of these networks and offers Python code implementations for each. The final chapter of the book introduces Transformers, a revolutionary model that has had a significant impact on natural language processing (NLP). This chapter provides you with a thorough understanding of how Transformers work and includes Python code implementations. By the end of the book, you will be able to use deep learning to solve real-world problems. WHAT YOU WILL LEARN ● Develop a comprehensive understanding of neural networks' key concepts and principles. ● Gain proficiency in Python as you code and implement major deep-learning algorithms from scratch. ● Build and implement predictive models using various neural networks ● Learn how to use Transformers for complex NLP tasks ● Explore techniques to enhance the performance of your deep learning models. WHO THIS BOOK IS FOR This book is for anyone who is interested in a career in emerging technologies, such as artificial intelligence (AI), data analytics, machine learning, deep learning, and data science. It is a comprehensive guide that covers the fundamentals of these technologies, as well as the skills and knowledge that you need to succeed in this field. TABLE OF CONTENTS 1. Python for Data Science 2. Real-World Challenges for Data Professionals in Converting Data Into Insights 3. Build a Neural Network-Based Predictive Model 4. Convolutional Neural Networks 5. Optical Character Recognition 6. Object Detection 7. Image Segmentation 8. Recurrent Neural Networks 9. Generative Adversarial Networks 10. Transformers
Author: David Paper Publisher: Apress ISBN: 1484253736 Category : Computers Languages : en Pages : 247
Book Description
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: Kyran Dale Publisher: "O'Reilly Media, Inc." ISBN: 1098111842 Category : Computers Languages : en Pages : 569
Book Description
How do you turn raw, unprocessed, or malformed data into dynamic, interactive web visualizations? In this practical book, author Kyran Dale shows data scientists and analysts--as well as Python and JavaScript developers--how to create the ideal toolchain for the job. By providing engaging examples and stressing hard-earned best practices, this guide teaches you how to leverage the power of best-of-breed Python and JavaScript libraries. Python provides accessible, powerful, and mature libraries for scraping, cleaning, and processing data. And while JavaScript is the best language when it comes to programming web visualizations, its data processing abilities can't compare with Python's. Together, these two languages are a perfect complement for creating a modern web-visualization toolchain. This book gets you started. You'll learn how to: Obtain data you need programmatically, using scraping tools or web APIs: Requests, Scrapy, Beautiful Soup Clean and process data using Python's heavyweight data processing libraries within the NumPy ecosystem: Jupyter notebooks with pandas+Matplotlib+Seaborn Deliver the data to a browser with static files or by using Flask, the lightweight Python server, and a RESTful API Pick up enough web development skills (HTML, CSS, JS) to get your visualized data on the web Use the data you've mined and refined to create web charts and visualizations with Plotly, D3, Leaflet, and other libraries
Author: Osvaldo Martin Publisher: Packt Publishing Ltd ISBN: 1785889850 Category : Computers Languages : en Pages : 282
Book Description
Unleash the power and flexibility of the Bayesian framework About This Book Simplify the Bayes process for solving complex statistical problems using Python; Tutorial guide that will take the you through the journey of Bayesian analysis with the help of sample problems and practice exercises; Learn how and when to use Bayesian analysis in your applications with this guide. Who This Book Is For Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement probabilistic models in their day to day projects. Programming experience with Python is essential. No previous statistical knowledge is assumed. What You Will Learn Understand the essentials Bayesian concepts from a practical point of view Learn how to build probabilistic models using the Python library PyMC3 Acquire the skills to sanity-check your models and modify them if necessary Add structure to your models and get the advantages of hierarchical models Find out how different models can be used to answer different data analysis questions When in doubt, learn to choose between alternative models. Predict continuous target outcomes using regression analysis or assign classes using logistic and softmax regression. Learn how to think probabilistically and unleash the power and flexibility of the Bayesian framework In Detail The purpose of this book is to teach the main concepts of Bayesian data analysis. We will learn how to effectively use PyMC3, a Python library for probabilistic programming, to perform Bayesian parameter estimation, to check models and validate them. This book begins presenting the key concepts of the Bayesian framework and the main advantages of this approach from a practical point of view. Moving on, we will explore the power and flexibility of generalized linear models and how to adapt them to a wide array of problems, including regression and classification. We will also look into mixture models and clustering data, and we will finish with advanced topics like non-parametrics models and Gaussian processes. With the help of Python and PyMC3 you will learn to implement, check and expand Bayesian models to solve data analysis problems. Style and approach Bayes algorithms are widely used in statistics, machine learning, artificial intelligence, and data mining. This will be a practical guide allowing the readers to use Bayesian methods for statistical modelling and analysis using Python.
Author: Naomi Greene Publisher: Hong Kong University Press ISBN: 9888208691 Category : Performing Arts Languages : en Pages : 281
Book Description
Throughout the twentieth century, American filmmakers have embraced cinematic representations of China. Beginning with D.W. Griffith’s silent classicBroken Blossoms (1919) and ending with the computer-animated Kung Fu Panda (2008), this book explores China’s changing role in the American imagination. Taking viewers into zones that frequently resist logical expression or more orthodox historical investigation, the films suggest the welter of intense and conflicting impulses that have surrounded China. They make clear that China has often served as the very embodiment of “otherness”—a kind of yardstick or cloudy mirror of America itself. It is a mirror that reflects not only how Americans see the racial “other” but also a larger landscape of racial, sexual, and political perceptions that touch on the ways in which the nation envisions itself and its role in the world. In the United States, the exceptional emotional charge that imbues images of China has tended to swing violently from positive to negative and back again: China has been loved and—as is generally the case today—feared. Using film to trace these dramatic fluctuations, author Naomi Greene relates them to the larger arc of historical and political change. Suggesting that filmic images both reflect and fuel broader social and cultural impulses, she argues that they reveal a constant tension or dialectic between the “self” and the “other.” Significantly, with the important exception of films made by Chinese or Chinese American directors, the Chinese other is almost invariably portrayed in terms of the American self. Placed in a broader context, this ethnocentrism is related both to an ever-present sense of American exceptionalism and to a Manichean world view that perceives other countries as friends or enemies. “From Fu Manchu to Kung Fu Panda chronicles the struggle within Hollywood film to come to grips with American ambivalence toward China as a nation against the backdrop of its current economic and geopolitical ascendancy on the world stage. Reaching back to early film portrayals of Chinatown, Christian missionaries, warlords, and perverse villains bent on world domination, Greene moves from the ‘yellow peril’ to the ‘red menace’ as she examines WWII and Cold War cinema. She also explores the range of film fantasies circulating today, from films about Tibet to Chinese American independent features and the global popularity of kung fu cartoons. This accessible book allows these films to speak to the post 9-11/Occupy Wall Street generation and makes a welcome contribution to debates about Hollywood Orientalism and transnational Chinese film connections.” —Gina Marchetti, author of The Chinese Diaspora on American Screens: Race, Sex, and Cinema “A significant work of filmography, Naomi Greene’s book explores the exotic, at times menacing, but always fantastic images of China flickering on the silver screen of the American imagination. The author writes lucidly, jargon-free, and with the sure-footedness of a seasoned scholar.” —Yunte Huang, author of Charlie Chan: The Untold Story of the Honorable Detective and His Rendezvous with American History
Author: Pratap Dangeti Publisher: Packt Publishing Ltd ISBN: 1789957222 Category : Computers Languages : en Pages : 676
Book Description
Understand, explore, and effectively present data using the powerful data visualization techniques of Python Key FeaturesUse the power of Pandas and Matplotlib to easily solve data mining issuesUnderstand the basics of statistics to build powerful predictive data modelsGrasp data mining concepts with helpful use-cases and examplesBook Description Data mining, or parsing the data to extract useful insights, is a niche skill that can transform your career as a data scientist Python is a flexible programming language that is equipped with a strong suite of libraries and toolkits, and gives you the perfect platform to sift through your data and mine the insights you seek. This Learning Path is designed to familiarize you with the Python libraries and the underlying statistics that you need to get comfortable with data mining. You will learn how to use Pandas, Python's popular library to analyze different kinds of data, and leverage the power of Matplotlib to generate appealing and impressive visualizations for the insights you have derived. You will also explore different machine learning techniques and statistics that enable you to build powerful predictive models. By the end of this Learning Path, you will have the perfect foundation to take your data mining skills to the next level and set yourself on the path to become a sought-after data science professional. This Learning Path includes content from the following Packt products: Statistics for Machine Learning by Pratap DangetiMatplotlib 2.x By Example by Allen Yu, Claire Chung, Aldrin YimPandas Cookbook by Theodore PetrouWhat you will learnUnderstand the statistical fundamentals to build data modelsSplit data into independent groups Apply aggregations and transformations to each groupCreate impressive data visualizationsPrepare your data and design models Clean up data to ease data analysis and visualizationCreate insightful visualizations with Matplotlib and SeabornCustomize the model to suit your own predictive goalsWho this book is for If you want to learn how to use the many libraries of Python to extract impactful information from your data and present it as engaging visuals, then this is the ideal Learning Path for you. Some basic knowledge of Python is enough to get started with this Learning Path.
Author: Felicia Zopol Publisher: Quirk Books ISBN: 1594747725 Category : Humor Languages : en Pages : 212
Book Description
At Last! A Comprehensive Guide to Sexual Intercourse! Sex is as old as human civilization—so why, after all these years, are the secrets of a rewarding sex life so elusive? Fortunately, The Sex Instruction Manual is here to answer all of your most pressing questions: Why do men fall asleep after achieving orgasm? What’s the G-spot and where can I find it? How can I introduce sex toys into my relationship? Are there really condoms designed for women? And what in the world is “doorknobbing”? You’ll find answers to all of these questions and more, courtesy of author and celebrated “sexpert” Felicia Zopol.
Author: Brian Luff
Author: Brian Luff
Author: Daniel Y. Chen
Author: Shekhar Khandelwal
Author: David Paper
Author: Kyran Dale
Author: Wes McKinney
Author: Osvaldo Martin
Author: Naomi Greene
Author: Pratap Dangeti
Author: Felicia Zopol