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Deep Learning with Python: A Hands-on Introduction
Deep Learning with Python: A Hands-on Introduction
Discover the practical aspects of implementing deep-learning solutions using the rich Python ecosystem. This book bridges the gap between the academic state-of-the-art and the industry state-of-the-practice by introducing you to deep learning frameworks such as Keras, Theano, and Caffe. The practicalities of these frameworks is often...
Advanced Analytics with Spark: Patterns for Learning from Data at Scale
Advanced Analytics with Spark: Patterns for Learning from Data at Scale

In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example.

You’ll start with an...

Python Machine Learning Case Studies: Five Case Studies for the Data Scientist
Python Machine Learning Case Studies: Five Case Studies for the Data Scientist
Embrace machine learning approaches and Python to enable automatic rendering of rich insights and solve business problems. The book uses a hands-on case study-based approach to crack real-world applications to which machine learning concepts can be applied. These smarter machines will enable your business processes to achieve efficiencies on...
A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering)
A Primer on Scientific Programming with Python (Texts in Computational Science and Engineering)

The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and...

Unsupervised Learning with R
Unsupervised Learning with R

Work with over 40 packages to draw inferences from complex datasets and find hidden patterns in raw unstructured data

About This Book

  • Unlock and discover how to tackle clusters of raw data through practical examples in R
  • Explore your data and create your own models from scratch
  • ...
The Healthy Programmer: Get Fit, Feel Better, and Keep Coding (Pragmatic Programmers)
The Healthy Programmer: Get Fit, Feel Better, and Keep Coding (Pragmatic Programmers)

Printed in full color.

To keep doing what you love, you need to maintain your own systems, not just the ones you write code for. Regular exercise and proper nutrition help you learn, remember, concentrate, and be creative--skills critical to doing your job well. Learn how to change your work habits, master exercises
...

Digital Speech: Coding for Low Bit Rate Communication Systems, 2nd Edition
Digital Speech: Coding for Low Bit Rate Communication Systems, 2nd Edition

Building on the success of the first edition Digital Speech offers extensive new, updated and revised material based upon the latest research. This Second Edition continues to provide the fundamental technical background required for low bit rate speech coding and the hottest developments in digital speech coding techniques that...

Translating Statistics to Make Decisions: A Guide for the Non-Statistician
Translating Statistics to Make Decisions: A Guide for the Non-Statistician

Examine and solve the common misconceptions and fallacies that non-statisticians bring to their interpretation of statistical results. Explore the many pitfalls that non-statisticians―and also statisticians who present statistical reports to non-statisticians―must avoid if statistical results are to be correctly used for...

Pro Spark Streaming: The Zen of Real-Time Analytics Using Apache Spark
Pro Spark Streaming: The Zen of Real-Time Analytics Using Apache Spark

Learn the right cutting-edge skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. This book walks you through end-to-end real-time application development using real-world applications, data, and code. Taking an application-first approach, each chapter introduces use cases from...

A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R
A Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R

The only how-to guide offering a unified, systemic approach to acquiring, cleaning, and managing data in R

Every experienced practitioner knows that preparing data for modeling is a painstaking, time-consuming process. Adding to the difficulty is that most modelers learn the steps involved in cleaning and managing data...

Developing Analytic Talent: Becoming a Data Scientist
Developing Analytic Talent: Becoming a Data Scientist

Learn what it takes to succeed in the the most in-demand tech job

Harvard Business Review calls it the sexiest tech job of the 21st century. Data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented IT...

Docker for Data Science: Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server
Docker for Data Science: Building Scalable and Extensible Data Infrastructure Around the Jupyter Notebook Server
Learn Docker "infrastructure as code" technology to define a system for performing standard but non-trivial data tasks on medium- to large-scale data sets, using Jupyter as the master controller.

It is not uncommon for a real-world data set to fail to be easily managed. The set may not fit well into access memory or
...
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