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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlo...
by Aur茅lien G茅ron

Language

English

Pages

851

Publication Date

September 05, 2019

Product Description
Customer Reviews
<p>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.</p><p>By using concrete examples, minimal theory, and two production-ready Python frameworks鈥擲cikit-Learn and TensorFlow鈥攁uthor Aur茅lien G茅ron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You鈥檒l 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鈥檝e learned, all you need is programming experience to get started.</p><ul><li>Explore the machine learning landscape, particularly neural nets</li><li>Use Scikit-Learn to track an example machine-learning project end-to-end</li><li>Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods</li><li>Use the TensorFlow library to build and train neural nets</li><li>Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning</li><li>Learn techniques for training and scaling deep neural nets</li></ul>
Swipe to Unlock: The Primer on Technology and Business Strategy
by , Neel Mehta

Language

English

Pages

347

Publication Date

September 19, 2017

Product Description
Customer Reviews
<b>Authored by 3 Product Managers at Google, Facebook, and Microsoft,聽</b><i>Swipe to Unlock</i>聽is a comprehensive guide on the must-know concepts of technology and business strategy.聽<b>It is a must-read for anyone pursuing product management, design, marketing, consulting or business strategy roles in the tech industry.</b><br /><br />***Swipe to Unlock was updated in 2019 to <b>include over 40 pages of new content</b> to cover the latest developments in the world of tech.***<b> We highly recommend buying our book directly from Amazon rather than a third-party seller as it's the only way to ensure you get the latest version.</b><br /><br />This聽<b>#1 Amazon Business Bestseller won a medal聽</b>from the聽<b>North American Book Awards</b> and has been featured in聽<b>The Wall Street Journal</b>, <b>Forbes</b>,聽and聽<b>Business Insider.聽</b><i>Swipe to Unlock</i> was touted as聽<b>"our generation's Rosetta Stone for enabling anyone to peer into the technology changing everyday life"</b>聽by Jeremy Schifeling.<br /><ul><li>How does Spotify determine what songs to recommend to you?</li><li>How did KaiOS become the third largest mobile operating system in just two years since launching?</li><li>Why does Amazon offer free shipping with Prime if it loses them money?</li><li>How did a single typo take down 20% of the internet?</li><li>Why did Microsoft acquire LinkedIn?</li></ul>By answering real-world questions like this,聽<b><i>Swipe to Unlock</i>聽gives you a peek under the hood of the technology you use every day, decodes tech's biggest buzzwords, and shows you how technology is changing the society we live in for better or for worse.</b><br /><br /><b>Topics Covered:聽</b>Software Development, Business Models & Strategies, Economics, Hacking & Security, Hardware & Robots, The Internet, Cloud Computing, Big Data, Technology Policy, Emerging Markets, Future Trends, and much more!<br /><br /><b>Featured Companies:聽</b>Google, Facebook, Microsoft, Amazon, Apple, Spotify, Uber, WeChat, Yelp, Tinder, Washington Post, Grab, Toyota, GoJek, Samsung, Salesforce, M-Pesa, Quora, KaiOS, Twitter, Tesla, ByteDance, Airbnb, Robinhood, Adobe, Alibaba, Netflix, Paytm, Target, and many more!<br /><br /><b>Unlock the answers you need to ace your tech interviews or become a better-educated digital citizen.</b><br />
Don't Make Me Think, Revisited: A Common Sense Approach to Web Us...
by Steve Krug

Language

English

Pages

210

Publication Date

December 23, 2013

Product Description
Customer Reviews
Since<i> Don鈥檛 Make Me Think </i>was first published in 2000, hundreds of thousands of Web designers and developers have relied on usability guru Steve Krug鈥檚 guide to help them understand the principles of intuitive navigation and information design. Witty, commonsensical, and eminently practical, it鈥檚 one of the best-loved and most recommended books on the subject.<br /> <br />Now Steve returns with fresh perspective to reexamine the principles that made<i> Don鈥檛 Make Me Think</i> a classic鈥搘ith updated examples and a new chapter on mobile usability. And it鈥檚 still short, profusely illustrated鈥nd best of all鈥揻un to read.<br /> <br />If you鈥檝e read it before, you鈥檒l rediscover what made <i>Don鈥檛 Make Me Think</i> so essential to Web designers and developers around the world. If you鈥檝e never read it, you鈥檒l see why so many people have said it should be required reading for anyone working on Web sites.<br /> <br /> <br />鈥淎fter reading it over a couple of hours and putting its ideas to work for the past five years, I can say it has done more to improve my abilities as a Web designer than any other book.鈥?lt;br />鈥揓effrey Zeldman, author of Designing with Web Standards <p>聽</p>
Monolith to Microservices: Evolutionary Patterns to Transform You...
by Sam Newman

Language

English

Pages

272

Publication Date

November 14, 2019

Product Description
Customer Reviews
<p>How do you detangle a monolithic system and migrate it to a microservice architecture? How do you do it while maintaining business-as-usual? As a companion to Sam Newman鈥檚 extremely popular <i>Building Microservices</i>, this new book details a proven method for transitioning an existing monolithic system to a microservice architecture.</p><p>With many illustrative examples, insightful migration patterns, and a bevy of practical advice to transition your monolith enterprise into a microservice operation, this practical guide covers multiple scenarios and strategies for a successful migration, from initial planning all the way through application and database decomposition. You鈥檒l learn several tried and tested patterns and techniques that you can use as you migrate your existing architecture.</p><ul><li>Ideal for organizations looking to transition to microservices, rather than rebuild</li><li>Helps companies determine whether to migrate, when to migrate, and where to begin</li><li>Addresses communication, integration, and the migration of legacy systems</li><li>Discusses multiple migration patterns and where they apply</li><li>Provides database migration examples, along with synchronization strategies</li><li>Explores application decomposition, including several architectural refactoring patterns</li><li>Delves into details of database decomposition, including the impact of breaking referential and transactional integrity, new failure modes, and more</li></ul>
Database Internals: A Deep Dive into How Distributed Data Systems...
by Alex Petrov

Language

English

Pages

376

Publication Date

September 13, 2019

Product Description
Customer Reviews
<p>When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it鈥檚 often difficult to understand what each one offers and how they differ. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.</p><p>Throughout the book, you鈥檒l explore relevant material gleaned from numerous books, papers, blog posts, and the source code of several open source databases. These resources are listed at the end of parts one and two. You鈥檒l discover that the most significant distinctions among many modern databases reside in subsystems that determine how storage is organized and how data is distributed.</p><p>This book examines:</p><ul><li><b>Storage engines:</b> Explore storage classification and taxonomy, and dive into B-Tree-based and immutable Log Structured storage engines, with differences and use-cases for each</li><li><b>Storage building blocks:</b> Learn how database files are organized to build efficient storage, using auxiliary data structures such as Page Cache, Buffer Pool and Write-Ahead Log</li><li><b>Distributed systems:</b> Learn step-by-step how nodes and processes connect and build complex communication patterns</li><li><b>Database clusters:</b> Which consistency models are commonly used by modern databases and how distributed storage systems achieve consistency</li></ul>
Python for Data Analysis: Data Wrangling with Pandas, NumPy, and ...
by Wes McKinney

Language

English

Pages

550

Publication Date

September 25, 2017

Product Description
Customer Reviews
<p>Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You鈥檒l learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process.</p><p>Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It鈥檚 ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.</p><ul><li>Use the IPython shell and Jupyter notebook for exploratory computing</li><li>Learn basic and advanced features in NumPy (Numerical Python)</li><li>Get started with data analysis tools in the pandas library</li><li>Use flexible tools to load, clean, transform, merge, and reshape data</li><li>Create informative visualizations with matplotlib</li><li>Apply the pandas groupby facility to slice, dice, and summarize datasets</li><li>Analyze and manipulate regular and irregular time series data</li><li>Learn how to solve real-world data analysis problems with thorough, detailed examples</li></ul>
Ultimate Step by Step Guide to Machine Learning Using Python: Pre...
by Daneyal Anis

Language

English

Pages

Publication Date

February 16, 2020

Product Description
Customer Reviews
<h1>*Start your Data Science career using Python today!*</h1><br /><h2>Are you ready to start your new exciting career? Ready to crush your machine learning career goals?</h2><br /><br /><b><u>Are you overwhelmed with complexity of the books on this subject?</u></b><br /><br /><h1><i>Then let this breezy and fun little book on Python and machine learning models make you a data scientist in 7 days!</i></h1><br /><br />First part of this book introduces Python basics including:<br />鈥ata Structures like Pandas <br />鈥oundational libraries like Numpy, Seaborn and Scikit-Learn<br /><br />Second part of this book shows you how to build predictive machine learning models step by step using techniques such as:<br />鈥egression analysis<br />鈥ecision tree analysis<br />鈥raining and testing data models<br />鈥ensor Flow, Keras and PyTorch<br />鈥dditional data science concepts like Classification Analysis, Clustering, Association Learning and Dimension Reduction<br /><br />The final part of the book provides a structured framework on how to solve real world problems using data science and how to structure your data science project. <br /><br />After reading this book you will be able to:<br />鈥ode in Python with confidence<br />鈥uild new machine learning models from scratch<br />鈥now how to clean and prepare your data for analytics<br />鈥peak confidently about statistical analysis techniques<br /><br />Data Science was ranked the fast-growing field by LinkedIn and Data Scientist is one of the most highly sought after and lucrative careers in the world!<br /><br /><h2><b><i>If you are on the fence about making the leap to a new and lucrative career, this is the book for you!</i></b></h2><br /><br /><b>What sets this book apart from other books on the topic of Python and Machine learning: </b><br />鈥tep by step code examples and explanation<br />鈥omplex concepts explained visually<br />鈥eal world applicability of the machine learning models introduced<br />鈥onus free code samples that you can try yourself without any prior experience in Python!<br /><br /><br /><b>What do I need to get started?</b><br /><br />You will have a step by step action plan in place once you finish this book and finally feel that you, can master data science and machine learning and start lucrative and rewarding career! <br /><br />Ready to dive in to the exciting world of Python and Machine Learning?<br /><br /><b><u>Then scroll up to the top and hit that BUY BUTTON!</u></b><br /><br />
Code: The Hidden Language of Computer Hardware and Software (Deve...
by Charles Petzold

Language

English

Pages

400

Publication Date

October 11, 2000

Product Description
Customer Reviews
<p>What do flashlights, the British invasion, black cats, and seesaws have to do with computers? In CODE, they show us the ingenious ways we manipulate language and invent new means of communicating with each other. And through CODE, we see how this ingenuity and our very human compulsion to communicate have driven the technological innovations of the past two centuries. <br /> Using everyday objects and familiar language systems such as Braille and Morse code, author Charles Petzold weaves an illuminating narrative for anyone who鈥檚 ever wondered about the secret inner life of computers and other smart machines. <br /> It鈥檚 a cleverly illustrated and eminently comprehensible story鈥攁nd along the way, you鈥檒l discover you鈥檝e gained a real context for understanding today鈥檚 world of PCs, digital media, and the Internet. No matter what your level of technical savvy, CODE will charm you鈥攁nd perhaps even awaken the technophile within.
Building Microservices: Designing Fine-Grained Systems
by Sam Newman

Language

English

Pages

280

Publication Date

February 02, 2015

Product Description
Customer Reviews
<p>Distributed systems have become more fine-grained in the past 10 years, shifting from code-heavy monolithic applications to smaller, self-contained microservices. But developing these systems brings its own set of headaches. With lots of examples and practical advice, this book takes a holistic view of the topics that system architects and administrators must consider when building, managing, and evolving microservice architectures.</p><p>Microservice technologies are moving quickly. Author Sam Newman provides you with a firm grounding in the concepts while diving into current solutions for modeling, integrating, testing, deploying, and monitoring your own autonomous services. You鈥檒l follow a fictional company throughout the book to learn how building a microservice architecture affects a single domain.</p><ul><li>Discover how microservices allow you to align your system design with your organization鈥檚 goals</li><li>Learn options for integrating a service with the rest of your system</li><li>Take an incremental approach when splitting monolithic codebases</li><li>Deploy individual microservices through continuous integration</li><li>Examine the complexities of testing and monitoring distributed services</li><li>Manage security with user-to-service and service-to-service models</li><li>Understand the challenges of scaling microservice architectures</li></ul>
Data Science from Scratch: First Principles with Python
by Joel Grus

Language

English

Pages

408

Publication Date

April 12, 2019

Product Description
Customer Reviews
<p>To really learn data science, you should not only master the tools鈥攄ata science libraries, frameworks, modules, and toolkits鈥攂ut also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch.</p><p>If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today鈥檚 messy glut of data.</p><ul><li>Get a crash course in Python</li><li>Learn the basics of linear algebra, statistics, and probability鈥攁nd how and when they鈥檙e used in data science</li><li>Collect, explore, clean, munge, and manipulate data</li><li>Dive into the fundamentals of machine learning</li><li>Implement models such as k-nearest neighbors, Na茂ve Bayes, linear and logistic regression, decision trees, neural networks, and clustering</li><li>Explore recommender systems, natural language processing, network analysis, MapReduce, and databases</li></ul>

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