These deals are good for today only, so be sure to take advantage of the pricing before the offers expire.
Free Packt eBook by Aidas Bendoraitis (valid through 11/19 at 19:00 EST). This book covers Django 1.8, Haystack, Django CMS, Python.
Over 90 practical recipes to help you create scalable websites using the Django 1.8 framework
Django is a web framework that was designed to strike a balance between rapid web development and high performance. It has the capacity to handle applications with high levels of user traffic and interaction, and can integrate with massive databases on the backend, constantly collecting and processing data in real time.
By the end of this book, you will have a good understanding of the new features added to Django 1.8 and be an expert at web development processes.
What You Will Learn
- Get started with the basic configuration necessary to start any Django project
- Build a database structure out of reusable model mixins
- Manage forms and views and get to know some useful patterns that are used to create them
- Create handy template filters and tags that you can reuse in every project
- Integrate your own functionality into the Django CMS
- Manage hierarchical structures with MPTT
- Import data from local sources and external web services as well as exporting your data to third parties
- Implement a multilingual search with Haystack
- Test and deploy your project efficiently
About the Author
Aidas Bendoraitis has been professionally working with web technologies for over a decade. Over the past nine years at a Berlin-based company, studio 38 pure communication GmbH, he has developed a number of small-scale and large-scale Django projects—mostly in the cultural area—together with a creative team. At the moment, he is also working as a software architect at a London-based mobile startup, Hype.
Aidas regularly attends meetups of Django User Group Berlin, occasionally visits Django and Python conferences, and writes a weblog about Django: https://djangotricks.blogspot.com/.
$19.99 How to Use Objects
$19.99 InformIT eBook by Holger Gast. This book covers Object-Oriented Programming, Observer Pattern, Composite Pattern, Visitor Pattern, Interpreter Pattern, Stack Machines, Liskov Substitution Principal, Unit Testing, Model-View-Controller Pattern, State Machines, Single Responsibility Principal.
While most developers today use object-oriented languages, the full power of objects is available only to those with a deep understanding of the object paradigm. How to Use Objects will help you gain that understanding, so you can write code that works exceptionally well in the real world.
Author Holger Gast focuses on the concepts that have repeatedly proven most valuable and shows how to render those concepts in concrete code. Rather than settling for minimal examples, he explores crucial intricacies, clarifies easily misunderstood ideas, and helps you avoid subtle errors that could have disastrous consequences.
Gast addresses the technical aspects of working with languages, libraries, and frameworks, as well as the strategic decisions associated with patterns, contracts, design, and system architecture. He explains the roles of individual objects in a complete application, how they react to events and fulfill service requests, and how to transform excellent designs into excellent code. Using practical examples based on Eclipse, he also shows how tools can help you work more efficiently, save you time, and sometimes even write high-quality code for you.
Gast writes for developers who have at least basic experience: those who’ve finished an introductory programming course, a university computer science curriculum, or a first or second job assignment.
- Understanding what a professionally designed object really looks like
- Writing code that reflects your true intentions—and testing to make sure it does
- Applying language idioms and connotations to write more readable and maintainable code
- Using design-by-contract to write code that consistently does what it’s supposed to do
- Coding and architecting effective event-driven software
- Separating model and view, and avoiding common mistakes
- Mastering strategies and patterns for efficient, flexible design
- Ensuring predictable object collaboration via responsibility-driven design
About the Author
Holger Gast graduated with a degree in computer science from the University of Tübingen, Germany, in 2000, and received a Ph.D. with a dissertation on type systems for programming languages in 2005 (Tübingen). As a post doctoral fellow, he worked on formal correctness proofs for software and finished his Habilitation for Computer Science in 2012 (Tübingen).
Since 2000, he has been teaching in the area of software engineering at different levels of the computer science curriculum, starting from introductory programming courses to lectures on software design and architecture. His other interests include scientific databases for the humanities and the model-driven construction of data-driven web applications.
$9.99 Disruptive Analytics Charting Your Strategy for Next-Generation Business Analytics
$9.99 Apress eBook by Thomas W. Dinsmore. This book covers Business Analytics, Hadoop, In-Memory Analytics, Streaming Analytics, Machine Learning, Self-Service Analytics.
- Uses open source computing to slash total cost of ownership
- Shows how to extract business value from the latest generation of machine learning techniques
- Shows how to reproduce the successes of today’s leaders at leveraging predictive analytics for more effective marketing, reduced credit risk, more efficient operations, and deeper insight about customers
Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities.
Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization.
Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today.
What You’ll Learn
- Discover how the open source business model works and how to make it work for you
- See how cloud computing completely changes the economics of analytics
- Harness the power of Hadoop and its ecosystem
- Find out why Apache Spark is everywhere
- Discover the potential of streaming and real-time analytics
- Learn what Deep Learning can do and why it matters
- See how self-service analytics can change the way organizations do business
Who This Book Is For
Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.
About the Author
Thomas W. Dinsmore is Knowledge Expert in Customer Analytics at The Boston Consulting Group. He previously served as Director of Product Management for Revolution Analytics; Analytics Solution Architect for IBM Big Data Solutions; and Principal Consultant for SAS Professional Services.
Dinsmore has more than twenty-five years of experience in predictive analytics. He led or contributed to analytic solutions for more than five hundred clients across vertical markets—including AT&T, Banco Santander, Citibank, Dell, J. C. Penney, Monsanto, Morgan Stanley, Office Depot, Sony, Staples, United Health Group, UBS, and Vodafone—and around the world—including the United States, Puerto Rico, Canada, Mexico, Venezuela, Brazil, Chile, the United Kingdom, Belgium, Spain, Italy, Turkey, Israel, Malaysia, and Singapore.
Although his roots are in hands-on customer analytics, in the past fifteen years Dinsmore has expanded the scope of his experience to include analytic software applications and broader solutions including database integration and web applications.
As a project lead, he has worked with DB2, Oracle, Netezza, SQL Server, and Teradata. Dinsmore is certified in SAS 9 and has working experience with the Hadoop ecosystem and the leading analytic tools in the market today, including SAS, R, SPSS, and Oracle Data Mining.
Dinsmore is the author of Modern Analytics Methodologies (FT Press, 2014) and Advanced Analytics Methodologies (FT Press, 2014) and runs The Big Analytics Blog. He holds his MBA from the Wharton School, The University of Pennsylvania, and his bachelor’s from Boston University.
50% off Manning’s eBook by Douglas G. McIlwraith, Haralambos Marmanis, Dmitry Babenko with foreword by Yike Guo. This book covers Web Data Analysis, Machine Learning, Neural Networks, Deep Learning, Recommendation Engines, Scikit-learn, Python, K-Means Algorithm, Gaussian Mixture Model, User-Based Collaborative Filtering, Singular Value Decomposition, Logistic Regression, Click Prediction, Vowpal Wabbit, Restricted Boltzmann Machine, A/B Testing, Bayesian Bandit.
Algorithms of the Intelligent Web, Second Edition teaches the most important approaches to algorithmic web data analysis, enabling you to create your own machine learning applications that crunch, munge, and wrangle data collected from users, web applications, sensors and website logs.
About the technology
Valuable insights are buried in the tracks web users leave as they navigate pages and applications. You can uncover them by using intelligent algorithms like the ones that have earned Facebook, Google, and Twitter a place among the giants of web data pattern extraction.
About the book
Algorithms of the Intelligent Web, Second Edition teaches you how to create machine learning applications that crunch and wrangle data collected from users, web applications, and website logs. In this totally revised edition, you’ll look at intelligent algorithms that extract real value from data. Key machine learning concepts are explained with code examples in Python’s scikit-learn. This book guides you through algorithms to capture, store, and structure data streams coming from the web. You’ll explore recommendation engines and dive into classification via statistical algorithms, neural networks, and deep learning.
- Introduction to machine learning
- Extracting structure from data
- Deep learning and neural networks
- How recommendation engines work
About the reader
Knowledge of Python is assumed.
About the authors
Douglas McIlwraith is a machine learning expert and data science practitioner in the field of online advertising.
Dr. Haralambos Marmanis is a pioneer in the adoption of machine learning techniques for industrial solutions.
Dmitry Babenko designs applications for banking, insurance, and supply-chain management.
GET MORE WITH MANNING
An eBook copy of the previous edition, Algorithms of the Intelligent Web (First Edition), is included at no additional cost. It will be automatically added to your Manning Bookshelf within 24 hours of purchase.
50% off Practical Recommender Systems
50% off Manning’s eBook by Kim Falk. This book covers Recommender Systems.
Practical Recommender Systems goes behind the curtain to show you how recommender systems work and, more importantly, how to create and apply them for your site. After you’ve covered the basics of how recommender systems work, you’ll discover how to collect user data and produce personalized recommendations. Next, you’ll learn how and where to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, this hands-on guide covers scaling problems and other issues you may encounter as your site grows.
About the technology
Recommender systems are everywhere, helping you find everything from movies to jobs, restaurants to hospitals, even romance. Using behavioral and demographic data, these systems make predictions about what users will be most interested in at a particular time, resulting in high-quality, ordered, personalized suggestions. Recommender systems are practically a necessity for keeping your site content current, useful, and interesting to your visitors.
- Practical introduction to recommender system algorithms
- Collaborative and content-based filtering
- Creating individual recommendations from visitor data
- Real-world examples of recommender systems
About the reader
This book assumes you’re comfortable reading code in Python and have some experience with databases.
About the author
Kim Falk is a Data Scientist at Adform, where he is working on recommender systems. He has experience in providing recommendations for large entertainment companies and working with big data solutions.
50% off Taming Text How to Find, Organize, and Manipulate It
50% off Manning’s eBook by Grant S. Ingersoll, Thomas S. Morton, Andrew L. Farris with foreword by Liz Liddy. This book covers Unstructured Text, Apache Solr, Fuzzy String Matching, Named-Entity Recognition, OpenNLP, Clustering Text, Apache Mahout.
Taming Text is a hands-on, example-driven guide to working with unstructured text in the context of real-world applications. This book explores how to automatically organize text using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. The book guides you through examples illustrating each of these topics, as well as the foundations upon which they are built.
About the book
There is so much text in our lives, we are practically drowning in it. Fortunately, there are innovative tools and techniques for managing unstructured information that can throw the smart developer a much-needed lifeline. You’ll find them in this book.
Taming Text is a practical, example-driven guide to working with text in real applications. This book introduces you to useful techniques like full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. You’ll explore real use cases as you systematically absorb the foundations upon which they are built.
Written in a clear and concise style, this book avoids jargon, explaining the subject in terms you can understand without a background in statistics or natural language processing. Examples are in Java, but the concepts can be applied in any language.
- When to use text-taming techniques
- Important open-source libraries like Solr and Mahout
- How to build text-processing applications
About the authors
Grant Ingersoll is an engineer, speaker, and trainer, a Lucene committer, and a cofounder of the Mahout machine-learning project.
Thomas Morton is the primary developer of OpenNLP and Maximum Entropy.
Drew Farris is a technology consultant, soft ware developer, and contributor to Mahout, Lucene, and Solr.
- Customer Service Training 101, 3rd Edition (Book) by Renee Evenson
- The Art of Unit Testing Video Edition (Video) by Roy Osherove
- Linux for Embedded and Real-time Applications, 4th Edition (Book) by Doug Abbott
O’Reilly Media, Inc.
- HTTP protocols (Book) by Ilya Grigorik
- Learning Microsoft Azure Storage (Book) by Mohamed Waly
- Practical Data Wrangling (Book) by Allan Visochek
- scikit-learn Cookbook - Second Edition (Book) by Julian Avila
- ASP.NET Core in 24 Hours, Sams Teach Yourself (Book) by Jeffrey T. Fritz
- Introduction to Steganography (Video) by Zacharias Voulgaris
- The Packer Book (Book) by James Turnbull