Cleaning Data for Effective Data Science

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Publisher : Packt Publishing Ltd
ISBN 13 : 1801074402
Total Pages : 499 pages
Book Rating : 4.8/5 (1 download)

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Book Synopsis Cleaning Data for Effective Data Science by : David Mertz

Download or read book Cleaning Data for Effective Data Science written by David Mertz and published by Packt Publishing Ltd. This book was released on 2021-03-31 with total page 499 pages. Available in PDF, EPUB and Kindle. Book excerpt: Think about your data intelligently and ask the right questions Key FeaturesMaster data cleaning techniques necessary to perform real-world data science and machine learning tasksSpot common problems with dirty data and develop flexible solutions from first principlesTest and refine your newly acquired skills through detailed exercises at the end of each chapterBook Description Data cleaning is the all-important first step to successful data science, data analysis, and machine learning. If you work with any kind of data, this book is your go-to resource, arming you with the insights and heuristics experienced data scientists had to learn the hard way. In a light-hearted and engaging exploration of different tools, techniques, and datasets real and fictitious, Python veteran David Mertz teaches you the ins and outs of data preparation and the essential questions you should be asking of every piece of data you work with. Using a mixture of Python, R, and common command-line tools, Cleaning Data for Effective Data Science follows the data cleaning pipeline from start to end, focusing on helping you understand the principles underlying each step of the process. You'll look at data ingestion of a vast range of tabular, hierarchical, and other data formats, impute missing values, detect unreliable data and statistical anomalies, and generate synthetic features. The long-form exercises at the end of each chapter let you get hands-on with the skills you've acquired along the way, also providing a valuable resource for academic courses. What you will learnIngest and work with common data formats like JSON, CSV, SQL and NoSQL databases, PDF, and binary serialized data structuresUnderstand how and why we use tools such as pandas, SciPy, scikit-learn, Tidyverse, and BashApply useful rules and heuristics for assessing data quality and detecting bias, like Benford’s law and the 68-95-99.7 ruleIdentify and handle unreliable data and outliers, examining z-score and other statistical propertiesImpute sensible values into missing data and use sampling to fix imbalancesUse dimensionality reduction, quantization, one-hot encoding, and other feature engineering techniques to draw out patterns in your dataWork carefully with time series data, performing de-trending and interpolationWho this book is for This book is designed to benefit software developers, data scientists, aspiring data scientists, teachers, and students who work with data. If you want to improve your rigor in data hygiene or are looking for a refresher, this book is for you. Basic familiarity with statistics, general concepts in machine learning, knowledge of a programming language (Python or R), and some exposure to data science are helpful.

Learning Spark

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Publisher : O'Reilly Media
ISBN 13 : 1492050016
Total Pages : 400 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Learning Spark by : Jules S. Damji

Download or read book Learning Spark written by Jules S. Damji and published by O'Reilly Media. This book was released on 2020-07-16 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow

Data Science on AWS

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492079367
Total Pages : 524 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Data Science on AWS by : Chris Fregly

Download or read book Data Science on AWS written by Chris Fregly and published by "O'Reilly Media, Inc.". This book was released on 2021-04-07 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more

Data Science Projects with Python

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 183855260X
Total Pages : 374 pages
Book Rating : 4.8/5 (385 download)

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Book Synopsis Data Science Projects with Python by : Stephen Klosterman

Download or read book Data Science Projects with Python written by Stephen Klosterman and published by Packt Publishing Ltd. This book was released on 2019-04-30 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain hands-on experience with industry-standard data analysis and machine learning tools in Python Key FeaturesTackle data science problems by identifying the problem to be solvedIllustrate patterns in data using appropriate visualizationsImplement suitable machine learning algorithms to gain insights from dataBook Description Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools, by applying them to realistic data problems. You will learn how to use pandas and Matplotlib to critically examine datasets with summary statistics and graphs, and extract the insights you seek to derive. You will build your knowledge as you prepare data using the scikit-learn package and feed it to machine learning algorithms such as regularized logistic regression and random forest. You’ll discover how to tune algorithms to provide the most accurate predictions on new and unseen data. As you progress, you’ll gain insights into the working and output of these algorithms, building your understanding of both the predictive capabilities of the models and why they make these predictions. By then end of this book, you will have the necessary skills to confidently use machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data. What you will learnInstall the required packages to set up a data science coding environmentLoad data into a Jupyter notebook running PythonUse Matplotlib to create data visualizationsFit machine learning models using scikit-learnUse lasso and ridge regression to regularize your modelsCompare performance between models to find the best outcomesUse k-fold cross-validation to select model hyperparametersWho this book is for If you are a data analyst, data scientist, or business analyst who wants to get started using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of Python and data analytics will help you get the most from this book. Familiarity with mathematical concepts such as algebra and basic statistics will also be useful.

The Species Seekers: Heroes, Fools, and the Mad Pursuit of Life on Earth

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Publisher : W. W. Norton & Company
ISBN 13 : 0393341321
Total Pages : 481 pages
Book Rating : 4.3/5 (933 download)

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Book Synopsis The Species Seekers: Heroes, Fools, and the Mad Pursuit of Life on Earth by : Richard Conniff

Download or read book The Species Seekers: Heroes, Fools, and the Mad Pursuit of Life on Earth written by Richard Conniff and published by W. W. Norton & Company. This book was released on 2011-10-25 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: Conniff tells the story of bold adventurers who risked death to discover strange life forms in the farthest corners of planet Earth.

Grokking Deep Learning

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Publisher : Simon and Schuster
ISBN 13 : 163835720X
Total Pages : 475 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Grokking Deep Learning by : Andrew W. Trask

Download or read book Grokking Deep Learning written by Andrew W. Trask and published by Simon and Schuster. This book was released on 2019-01-23 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Deep learning, a branch of artificial intelligence, teaches computers to learn by using neural networks, technology inspired by the human brain. Online text translation, self-driving cars, personalized product recommendations, and virtual voice assistants are just a few of the exciting modern advancements possible thanks to deep learning. About the Book Grokking Deep Learning teaches you to build deep learning neural networks from scratch! In his engaging style, seasoned deep learning expert Andrew Trask shows you the science under the hood, so you grok for yourself every detail of training neural networks. Using only Python and its math-supporting library, NumPy, you'll train your own neural networks to see and understand images, translate text into different languages, and even write like Shakespeare! When you're done, you'll be fully prepared to move on to mastering deep learning frameworks. What's inside The science behind deep learning Building and training your own neural networks Privacy concepts, including federated learning Tips for continuing your pursuit of deep learning About the Reader For readers with high school-level math and intermediate programming skills. About the Author Andrew Trask is a PhD student at Oxford University and a research scientist at DeepMind. Previously, Andrew was a researcher and analytics product manager at Digital Reasoning, where he trained the world's largest artificial neural network and helped guide the analytics roadmap for the Synthesys cognitive computing platform. Table of Contents Introducing deep learning: why you should learn it Fundamental concepts: how do machines learn? Introduction to neural prediction: forward propagation Introduction to neural learning: gradient descent Learning multiple weights at a time: generalizing gradient descent Building your first deep neural network: introduction to backpropagation How to picture neural networks: in your head and on paper Learning signal and ignoring noise:introduction to regularization and batching Modeling probabilities and nonlinearities: activation functions Neural learning about edges and corners: intro to convolutional neural networks Neural networks that understand language: king - man + woman == ? Neural networks that write like Shakespeare: recurrent layers for variable-length data Introducing automatic optimization: let's build a deep learning framework Learning to write like Shakespeare: long short-term memory Deep learning on unseen data: introducing federated learning Where to go from here: a brief guide

Data Science for Mathematicians

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Publisher : CRC Press
ISBN 13 : 0429675682
Total Pages : 545 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Data Science for Mathematicians by : Nathan Carter

Download or read book Data Science for Mathematicians written by Nathan Carter and published by CRC Press. This book was released on 2020-09-15 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science. As it applies to the curriculum, research, and career opportunities, data science is a fast-growing field. Contributors from both academics and industry present their views on these opportunities and how to advantage them.

Machine Learning with PyTorch and Scikit-Learn

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Publisher : Packt Publishing Ltd
ISBN 13 : 1801816387
Total Pages : 775 pages
Book Rating : 4.8/5 (18 download)

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Book Synopsis Machine Learning with PyTorch and Scikit-Learn by : Sebastian Raschka

Download or read book Machine Learning with PyTorch and Scikit-Learn written by Sebastian Raschka and published by Packt Publishing Ltd. This book was released on 2022-02-25 with total page 775 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch s simple to code framework. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Learn applied machine learning with a solid foundation in theory Clear, intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practices Book DescriptionMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. 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 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, we teach the principles allowing you to build models and applications for yourself. Why PyTorch? PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP). This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learn Explore frameworks, models, and techniques for machines to learn from data Use scikit-learn for machine learning and PyTorch for deep learning Train machine learning classifiers on images, text, and more Build and train neural networks, transformers, and boosting algorithms Discover best practices for evaluating and tuning models Predict continuous target outcomes using regression analysis Dig deeper into textual and social media data using sentiment analysis Who this book is for If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch. Before you get started with this book, you’ll need a good understanding of calculus, as well as linear algebra.

Data Science Projects with Python

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1800569440
Total Pages : 433 pages
Book Rating : 4.8/5 (5 download)

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Book Synopsis Data Science Projects with Python by : Stephen Klosterman

Download or read book Data Science Projects with Python written by Stephen Klosterman and published by Packt Publishing Ltd. This book was released on 2021-07-29 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain hands-on experience of Python programming with industry-standard machine learning techniques using pandas, scikit-learn, and XGBoost Key FeaturesThink critically about data and use it to form and test a hypothesisChoose an appropriate machine learning model and train it on your dataCommunicate data-driven insights with confidence and clarityBook Description If data is the new oil, then machine learning is the drill. As companies gain access to ever-increasing quantities of raw data, the ability to deliver state-of-the-art predictive models that support business decision-making becomes more and more valuable. In this book, you'll work on an end-to-end project based around a realistic data set and split up into bite-sized practical exercises. This creates a case-study approach that simulates the working conditions you'll experience in real-world data science projects. You'll learn how to use key Python packages, including pandas, Matplotlib, and scikit-learn, and master the process of data exploration and data processing, before moving on to fitting, evaluating, and tuning algorithms such as regularized logistic regression and random forest. Now in its second edition, this book will take you through the end-to-end process of exploring data and delivering machine learning models. Updated for 2021, this edition includes brand new content on XGBoost, SHAP values, algorithmic fairness, and the ethical concerns of deploying a model in the real world. By the end of this data science book, you'll have the skills, understanding, and confidence to build your own machine learning models and gain insights from real data. What you will learnLoad, explore, and process data using the pandas Python packageUse Matplotlib to create compelling data visualizationsImplement predictive machine learning models with scikit-learnUse lasso and ridge regression to reduce model overfittingEvaluate random forest and logistic regression model performanceDeliver business insights by presenting clear, convincing conclusionsWho this book is for Data Science Projects with Python – Second Edition is for anyone who wants to get started with data science and machine learning. If you're keen to advance your career by using data analysis and predictive modeling to generate business insights, then this book is the perfect place to begin. To quickly grasp the concepts covered, it is recommended that you have basic experience of programming with Python or another similar language, and a general interest in statistics.

The Notebooks of Leonardo Da Vinci (Complete)

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Author :
Publisher : Library of Alexandria
ISBN 13 : 1465514147
Total Pages : 1118 pages
Book Rating : 4.4/5 (655 download)

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Book Synopsis The Notebooks of Leonardo Da Vinci (Complete) by : Leonardo da Vinci

Download or read book The Notebooks of Leonardo Da Vinci (Complete) written by Leonardo da Vinci and published by Library of Alexandria. This book was released on 2020-09-28 with total page 1118 pages. Available in PDF, EPUB and Kindle. Book excerpt: A singular fatality has ruled the destiny of nearly all the most famous of Leonardo da Vinci's works. Two of the three most important were never completed, obstacles having arisen during his life-time, which obliged him to leave them unfinished; namely the Sforza Monument and the Wall-painting of the Battle of Anghiari, while the third—the picture of the Last Supper at Milan—has suffered irremediable injury from decay and the repeated restorations to which it was recklessly subjected during the XVIIth and XVIIIth centuries. Nevertheless, no other picture of the Renaissance has become so wellknown and popular through copies of every description. Vasari says, and rightly, in his Life of Leonardo, "that he laboured much more by his word than in fact or by deed", and the biographer evidently had in his mind the numerous works in Manuscript which have been preserved to this day. To us, now, it seems almost inexplicable that these valuable and interesting original texts should have remained so long unpublished, and indeed forgotten. It is certain that during the XVIth and XVIIth centuries their exceptional value was highly appreciated. This is proved not merely by the prices which they commanded, but also by the exceptional interest which has been attached to the change of ownership of merely a few pages of Manuscript. That, notwithstanding this eagerness to possess the Manuscripts, their contents remained a mystery, can only be accounted for by the many and great difficulties attending the task of deciphering them. The handwriting is so peculiar that it requires considerable practice to read even a few detached phrases, much more to solve with any certainty the numerous difficulties of alternative readings, and to master the sense as a connected whole. Vasari observes with reference to Leonardos writing: "he wrote backwards, in rude characters, and with the left hand, so that any one who is not practised in reading them, cannot understand them". The aid of a mirror in reading reversed handwriting appears to me available only for a first experimental reading. Speaking from my own experience, the persistent use of it is too fatiguing and inconvenient to be practically advisable, considering the enormous mass of Manuscripts to be deciphered. And as, after all, Leonardo's handwriting runs backwards just as all Oriental character runs backwards—that is to say from right to left—the difficulty of reading direct from the writing is not insuperable. This obvious peculiarity in the writing is not, however, by any means the only obstacle in the way of mastering the text. Leonardo made use of an orthography peculiar to himself; he had a fashion of amalgamating several short words into one long one, or, again, he would quite arbitrarily divide a long word into two separate halves; added to this there is no punctuation whatever to regulate the division and construction of the sentences, nor are there any accents—and the reader may imagine that such difficulties were almost sufficient to make the task seem a desperate one to a beginner. It is therefore not surprising that the good intentions of some of Leonardo s most reverent admirers should have failed.

Beard Science

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Publisher : Cipher Naught
ISBN 13 : 1942874243
Total Pages : 203 pages
Book Rating : 4.9/5 (428 download)

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Book Synopsis Beard Science by : Penny Reid

Download or read book Beard Science written by Penny Reid and published by Cipher Naught . This book was released on 2016-10-11 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: *Goodreads Choice Award Finalist for Best Romance * *Amazon Top 10 Romances of 2016* *AAR Top 10 Romances of All Time* From the NEW YORK TIMES, WALL STREET JOURNAL, & USA TODAY bestselling series. Make a deal with the devil and you might get what you want, but will it be what you need? Jennifer Sylvester wants one thing, and that one thing is NOT to be Tennessee’s reigning Banana Cake Queen. Ever the perpetual good girl and obedient daughter, Jennifer is buckling under the weight of her social media celebrity, her mother’s ambitions, and her father’s puritanical mandates. Jennifer is officially desperate. And desperate times call for Cletus Winston. Cletus Winston is a puzzle wrapped in a mystery covered in conundrum sauce, and now he’s in a pickle. Despite being convinced of his own omniscience, extortion by the exalted Banana Cake Queen of Green Valley has taken him completely by surprise. So... what’s a maniacal mastermind to do? Likely, the last thing you expect. Beard Science is book #3 in the Winston Brothers series. Each book is a standalone, full length (110k words), contemporary romantic comedy novel, and follows the romantic exploits and adventures of one of the six Winston Brothers.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow

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Publisher : "O'Reilly Media, Inc."
ISBN 13 : 149203259X
Total Pages : 851 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by : Aurélien Géron

Download or read book Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow written by Aurélien Géron and published by "O'Reilly Media, Inc.". This book was released on 2019-09-05 with total page 851 pages. Available in PDF, EPUB and Kindle. Book excerpt: Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets

Everything You Need to Ace U.S. History in One Big Fat Notebook, 2nd Edition

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Author :
Publisher : Workman Publishing Company
ISBN 13 : 1523520841
Total Pages : 594 pages
Book Rating : 4.5/5 (235 download)

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Book Synopsis Everything You Need to Ace U.S. History in One Big Fat Notebook, 2nd Edition by : Workman Publishing

Download or read book Everything You Need to Ace U.S. History in One Big Fat Notebook, 2nd Edition written by Workman Publishing and published by Workman Publishing Company. This book was released on 2023-04-11 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: From the brains behind Brain Quest comes the 2nd edition of the revolutionary U.S. history study guide. Updated to include recent history and revised to reflect a more complete, balanced recounting of historical events. Big Fat Notebooks offer the support of a knowledgeable teacher in the form of an approachable peer—the notes of smartest kid in class. Everything You Need to Ace U.S. History in One Big Fat Notebook is the same indispensable resource so many students depend on, updated with new and improved content covering Indigenous history in the U.S., the legacies of slavery, exploration, colonization, and imperialism, and significant current events through 2022, including the COVID-19 pandemic, political protests,, the most recent presidential election, and historic nominations to the Supreme Court. It will be the cutting-edge reference for students as education styles shift toward this informed approach to history. The Big Fat Notebooks meet Common Core State Standards, Next Generation Science Standards, and state history standards, and are vetted by National and State Teacher of the Year Award–winning teachers. They make learning fun, and are the perfect next step for every kid who grew up on Brain Quest.

Look Both Ways

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Publisher : Simon and Schuster
ISBN 13 : 1481438298
Total Pages : 240 pages
Book Rating : 4.4/5 (814 download)

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Book Synopsis Look Both Ways by : Jason Reynolds

Download or read book Look Both Ways written by Jason Reynolds and published by Simon and Schuster. This book was released on 2020-10-27 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: "A collection of ten short stories that all take place in the same day about kids walking home from school"--

UNIX and Linux System Administration Handbook

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Author :
Publisher : Addison-Wesley Professional
ISBN 13 : 0134278291
Total Pages : 1471 pages
Book Rating : 4.1/5 (342 download)

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Book Synopsis UNIX and Linux System Administration Handbook by : Evi Nemeth

Download or read book UNIX and Linux System Administration Handbook written by Evi Nemeth and published by Addison-Wesley Professional. This book was released on 2017-09-14 with total page 1471 pages. Available in PDF, EPUB and Kindle. Book excerpt: “As an author, editor, and publisher, I never paid much attention to the competition—except in a few cases. This is one of those cases. The UNIX System Administration Handbook is one of the few books we ever measured ourselves against.” —Tim O’Reilly, founder of O’Reilly Media “This edition is for those whose systems live in the cloud or in virtualized data centers; those whose administrative work largely takes the form of automation and configuration source code; those who collaborate closely with developers, network engineers, compliance officers, and all the other worker bees who inhabit the modern hive.” —Paul Vixie, Internet Hall of Fame-recognized innovator and founder of ISC and Farsight Security “This book is fun and functional as a desktop reference. If you use UNIX and Linux systems, you need this book in your short-reach library. It covers a bit of the systems’ history but doesn’t bloviate. It’s just straight-forward information delivered in a colorful and memorable fashion.” —Jason A. Nunnelley UNIX® and Linux® System Administration Handbook, Fifth Edition, is today’s definitive guide to installing, configuring, and maintaining any UNIX or Linux system, including systems that supply core Internet and cloud infrastructure. Updated for new distributions and cloud environments, this comprehensive guide covers best practices for every facet of system administration, including storage management, network design and administration, security, web hosting, automation, configuration management, performance analysis, virtualization, DNS, security, and the management of IT service organizations. The authors—world-class, hands-on technologists—offer indispensable new coverage of cloud platforms, the DevOps philosophy, continuous deployment, containerization, monitoring, and many other essential topics. Whatever your role in running systems and networks built on UNIX or Linux, this conversational, well-written ¿guide will improve your efficiency and help solve your knottiest problems.

Twilight of the Idols

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Author :
Publisher : Hackett Publishing
ISBN 13 : 1603848800
Total Pages : 130 pages
Book Rating : 4.6/5 (38 download)

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Book Synopsis Twilight of the Idols by : Friedrich Nietzsche

Download or read book Twilight of the Idols written by Friedrich Nietzsche and published by Hackett Publishing. This book was released on 1997-06-01 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: Twilight of the Idols presents a vivid, compressed overview of many of Nietzsche’s mature ideas, including his attack on Plato’s Socrates and on the Platonic legacy in Western philosophy and culture. Polt provides a trustworthy rendering of Nietzsche’s text in contemporary American English, complete with notes prepared by the translator and Tracy Strong. An authoritative Introduction by Strong makes this an outstanding edition. Select Bibliography and Index.

Data Science Live Book

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Publisher :
ISBN 13 : 9789874273666
Total Pages : pages
Book Rating : 4.2/5 (736 download)

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Book Synopsis Data Science Live Book by : Pablo Casas

Download or read book Data Science Live Book written by Pablo Casas and published by . This book was released on 2018-03-16 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a practical guide to problems that commonly arise when developing a machine learning project. The book's topics are: Exploratory data analysis Data Preparation Selecting best variables Assessing Model Performance More information on predictive modeling will be included soon. This book tries to demonstrate what it says with short and well-explained examples. This is valid for both theoretical and practical aspects (through comments in the code). This book, as well as the development of a data project, is not linear. The chapters are related among them. For example, the missing values chapter can lead to the cardinality reduction in categorical variables. Or you can read the data type chapter and then change the way you deal with missing values. You¿ll find references to other websites so you can expand your study, this book is just another step in the learning journey. It's open-source and can be found at http://livebook.datascienceheroes.com