- Books/Videos on Sale (or Free) Today
- New/Updated Safari Books and Courses
- New/Updated Pluralsight Courses
These deals are good for today only, so be sure to take advantage of the pricing before the offers expire.
Free Packt eBook by Ashish Kumar with foreword by Pradeep Gulipalli (valid through 11/15 at 19:00 EST). This book covers Predictive Analytics, Python.
Gain practical insights into predictive modelling by implementing Predictive Analytics algorithms on public datasets with Python
Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form - It needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Learning to predict who would win, lose, buy, lie, or die with Python is an indispensable skill set to have in this data age.
This book is your guide to getting started with Predictive Analytics using Python. You will see how to process data and make predictive models from it. We balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and numpy.
You’ll start by getting an understanding of the basics of predictive modeling, then you will see how to cleanse your data of impurities and get it ready it for predictive modeling. You will also learn more about the best predictive modeling algorithms such as Linear Regression, Decision Trees, and Logistic Regression. Finally, you will see the best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world.
What You Will Learn
- Understand the statistical and mathematical concepts behind Predictive Analytics algorithms and implement Predictive Analytics algorithms using Python libraries
- Analyze the result parameters arising from the implementation of Predictive Analytics algorithms
- Write Python modules/functions from scratch to execute segments or the whole of these algorithms
- Recognize and mitigate various contingencies and issues related to the implementation of Predictive Analytics algorithms
- Get to know various methods of importing, cleaning, sub-setting, merging, joining, concatenating, exploring, grouping, and plotting data with pandas and numpy
- Create dummy datasets and simple mathematical simulations using the Python numpy and pandas libraries
- Understand the best practices while handling datasets in Python and creating predictive models out of them
About the Author
Ashish Kumar is an IIM alumnus and an engineer at heart. He has extensive experience in data science, machine learning, and natural language processing having worked at organizations, such as McAfee-Intel, an ambitious data science startup Volt consulting), and presently associated to the software and research lab of a leading MNC. Apart from work, Ashish also participates in data science competitions at Kaggle in his spare time.
$9.99 Building a Comprehensive IT Security Program Practical Guidelines and Best Practices
$9.99 Apress eBook by Jeremy Wittkop. This book covers Information Security.
- Organizations continue to struggle with information security programs
- This book will demystify a lot of concepts around building effective information security programs
- This book will introduce concepts, ideas, and strategies that have been proven to be successful, but have not yet been published to a wide audience
- Organizations spend hundreds of thousands of dollars for the intelligence and thought leadership that will be provided in the book
- The book will cite historical examples and put the current situation in context in a way that it can be explained simply to people who may not be familiar with information security concepts
This book explains the ongoing war between private business and cyber criminals, state-sponsored attackers, terrorists, and hacktivist groups. Further, it explores the risks posed by trusted employees that put critical information at risk through malice, negligence, or simply making a mistake. It clarifies the historical context of the current situation as it relates to cybersecurity, the challenges facing private business, and the fundamental changes organizations can make to better protect themselves. The problems we face are difficult, but they are not hopeless.
Cybercrime continues to grow at an astounding rate. With constant coverage of cyber-attacks in the media, there is no shortage of awareness of increasing threats. Budgets have increased and executives are implementing stronger defenses. Nonetheless, breaches continue to increase in frequency and scope.
Building a Comprehensive IT Security Program shares why organizations continue to fail to secure their critical information assets and explains the internal and external adversaries facing organizations today. This book supplies the necessary knowledge and skills to protect organizations better in the future by implementing a comprehensive approach to security.
Jeremy Wittkop’s security expertise and critical experience provides insights into topics such as:
- Who is attempting to steal information and why?
- What are critical information assets?
- How are effective programs built?
- How is stolen information capitalized?
- How do we shift the paradigm to better protect our organizations?
- How we can make the cyber world safer for everyone to do business?
About the Author
Jeremy Wittkop is a leader in the information security industry, specifically as it relates to content and context protection. Jeremy brings insights from a variety of industries including, military and defense, logistics, entertainment, as well as information security services.
Jeremy started with Intelisecure as the leader of the Managed Services department and has overseen 1000% growth of that department by helping to solve complex Information Security challenges for organizations spanning the globe. Jeremy now leads Intelisecure’s Sales Engineering team, which is responsible for architecting solution packages that include creative approaches to people, process, and technology.
50% off Kafka in Action
50% off Manning’s eBook by Dylan Scott. This book covers Apache Kafka, Streaming Data.
In systems that handle big data, streaming data, or fast data, it’s important to get your data pipelines right. Apache Kafka is a wicked-fast distributed streaming platform that operates as more than just a persistent log or a flexible message queue. With Kafka, you can build the powerful real-time data processing pipelines required by modern distributed systems. Kafka in Action is a fast-paced introduction to every aspect of working with Kafka you need to really reap its benefits.
About the technology
Apache Kafka is a distributed streaming platform for logging and streaming data between services or applications. With Kafka, it’s easy to build applications that can act on or react to data streams as they flow through your system. Operational data monitoring, large scale message processing, website activity tracking, log aggregation, and more are all possible with Kafka. Open-source, easily scalable, durable when demand gets heavy, and fast - Kafka is perfect for developers who need total control of the data flowing into and through their applications. The demand for Kafka developers is at an all-time high, as companies like LinkedIn, The New York Times, and Netflix, are relying on Kafka where fast data is essential.
About the book
Kafka in Action is a practical, hands-on guide to building Kafka-based data pipelines. Filled with real-world use cases and scenarios, this book probes Kafka’s most common use cases, ranging from simple logging through managing streaming data systems for message routing, analytics, and more. Starting with an overview of Kafka’s core concepts, you’ll immediately learn how to set up and execute basic data movement tasks and how to record and consume streaming data. As you move through the examples in this book, you’ll learn the skills you need to work in a Kafka focused team with the ability to handle both developer and admin based tasks. At the end of this book, you’ll be more than ready to dig into even more advanced Kafka topics on your own, and happily able to use Kafka in your day-to-day workflow.
- Understanding Kafka’s concepts
- Implementing Kafka as a message queue
- Setting up and executing basic ETL tasks
- Recording and consuming streaming data
- Working with Kafka producers and consumers from Java applications
- Using Kafka as part of a large data project team
- Performing Kafka developer and admin tasks
About the reader
Written for intermediate Java developers or data engineers. No prior knowledge of Kafka is required.
About the author
Dylan Scott is a software developer with over ten years of experience in Java and Perl. His experience includes implementing Kafka as a messaging system for a large data migration, and he uses Kafka in his work in the insurance industry.
50% off Kafka Streams in Action
50% off Manning’s eBook by Bill Bejeck. This book covers Apache Kafka, Streaming Data.
Kafka Streams in Action teaches you everything you need to know to implement stream processing on data flowing into your Kafka platform, allowing you to focus on getting more from your data without sacrificing time or effort. Starting with a brief overview of Kafka and Stream Processing you’ll discover everything you need to know to develop with Kafka Streams: from its APIs, to creating your first app. Using real-world examples based on the most common uses of distributed processing you’ll learn to transform and collect data, work with multiple processors, aggregate data, and more. This book also teaches you about all important testing and integration techniques to ensure you’ll never have to sacrifice functionality. By the end of the book, you’ll be ready to use Kafka Streams in your projects to reap the benefits of the insight your data holds quickly and easily.
50% off Streaming Data Understanding the real-time pipeline
50% off Manning’s eBook by Andrew G. Psaltis. This book covers Streaming Data, Apache Spark, Apache Storm, Apache Flink, Apache Samza, Apache Kafka.
Streaming Data introduces the concepts and requirements of streaming and real-time data systems. The book is an idea-rich tutorial that teaches you to think about how to efficiently interact with fast-flowing data.
About the technology
As humans, we’re constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them.
About the book
Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you’ll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you’ll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation details.
- The right way to collect real-time data
- Architecting a streaming pipeline
- Analyzing the data
- Which technologies to use and when
About the reader
Written for developers familiar with relational database concepts. No experience with streaming or real-time applications required.
About the author
Andrew Psaltis is a software engineer focused on massively scalable real-time analytics.
Free Pluralsight course (one week) by Kobi Hikri. This course covers Data Analytics, Apache Kafka, Apache Cassandra, Apache Storm, Elasticsearch, Apache ZooKeeper.
In this course, Building an Enterprise Grade Distributed Online Analytics Platform, you’ll learn how to build a full-blown distributed analytics system using Kafka, Cassandra, Storm, and Elasticsearch. First, you’ll begin by understanding what is online analytics and how it differs from offline analytics. You’ll further discuss and analyze the parts of a modern online analytics system, including the data backbone, storage, processing, and insight generation. Next, you’ll develop an understanding of your choice of technology, its features, and why it was chosen for a specific task. Finally, you’ll explore how to properly integrate the technology into your solution in a manner that’s most beneficial. Each technology you use will be placed under an observant eye, and you’ll see how each technology provides scalability, fault tolerance, and most importantly how it contributes in achieving the functionality you desire. By the end of this course, you’ll be ready to immediately enrich your enterprise with amazing analytics capabilities.
About the Author
Kobi Hikri is a self-proclaimed software addict, providing a diverse range of professional software consultancy services for commercial clients worldwide. His commercial client-list spans a diverse range of industries, including: banking, human resource management, textual data analysis, image processing, and forensics. Kobi appreciates simple, elegant software architecture, with a focus on a deep understanding of the task at hand. He enjoys mentoring and teaching, and does it with passion. Kobi resides in the beautiful state of Israel, and is an avid nature lover. His hobbies include mountain biking and running.
- The Financial Advisor’s Success Manual (Book) by David Leo, Craig CMIEL
- Mastering Machine Learning with Python in Six Steps: A Practical Implementation Guide to Predictive Data Analytics Using Python (Book) by Manohar Swamynathan
- Processing Big Data with Azure HDInsight: Building Real-World Big Data Systems on Azure HDInsight Using the Hadoop Ecosystem (Book) by Vinit Yadav
- Raspberry Pi Supercomputing and Scientific Programming: MPI4PY, NumPy, and SciPy for Enthusiasts (Book) by Ashwin Pajankar
- Introduction to Video Production, 2nd Edition (Book) by Ronald J. Compesi, Jaime S. Gomez
- Exam Ref 70-745 Implementing a Software-Defined DataCenter (Book) by Jeff Graves, Joel Stidley
O’Reilly Media, Inc.
- Optimizing images (Book) by Lara Callender Hogan
- Practical Monitoring (Book) by Mike Julian
- Securing Open Source Libraries (Book) by Guy Podjarny
- Using Analytics to Inform Product Design (Video) by Matthew Edgar
- Beginning C# 7 Hands-On – The Core Language (Book) by Tom Owsiak
- Building Business Websites with Squarespace 7 - Second Edition (Book) by Miko Coffey
- Drupal 8 Module Development (Book) by Daniel Sipos
- Linux Device Drivers Development (Book) by John Madieu
- Mastering AWS Security (Book) by Albert Anthony
- Mastering iOS 11 Programming - Second Edition (Book) by Donny Wals
- Neural Network Programming with TensorFlow (Book) by Manpreet Singh Ghotra, Rajdeep Dua
- Practical Time Series Analysis (Book) by Dr. Avishek Pal, Dr. PKS Prakash
- Python Deep Learning Cookbook (Book) by Indra den Bakker
- Python Machine Learning - Second Edition (Book) by Sebastian Raschka, Vahid Mirjalili
- CSSLP®: Secure Software Implementation and Programming (Video) by Kevin Henry
- Illustrator CC Creating SVGs (Video) by William Everhart
- Sculpting a Character for Mobile Games (Video) by Jon Mills
- UX Design for Graphic Designers (Video) by Brett Marshall