Python Programming: A beginners’ guide to understand machine learning and master coding. Includes Smalltalk, Java, TCL, JavaScript, Perl, Scheme, Common Lisp, Data Science Analysis, C++, PHP & Ruby


(as of Jan 20,2020 02:50:46 UTC – Details)

Have you been seriously thinking about digging into programming but don’t know where to start? Are you looking for a quick boost to your career growth?

In this Python programming crash course, you will be guided by a quick and thorough introduction intended solely for beginners who want to understand Python programming and learn how to write helpful programs.
The book is aimed at getting you fast enough to accelerate and get you to write real programs in no moment. This book is also designed for programmers who have a vague language understanding and would like to brush up their knowledge before trying to program their Python hands-on.

The aim of this ultimate guide is to keep each section’s thoughts and provide step-by-step guidance to make the learning experience smooth and gradual.

It will also address how any future frustration can be reduced. Each code unit is tested, executed and re-read closely. In addition, the INTERACTIVE exercises are optimized for the highest level of commitment, meaning you’re not going to get bored to death. 

Here is what you will find in this book on Pythons for Beginners:

  • A History of Python and the basic concepts of Python Programming

  • How to prepare your computer for programming in Python and how to install Python on Windows, Mac, and Linux. Screenshots included.

  • Python functions that you’ll use often.

  • How to work with various data types including strings, lists, tuples, dictionaries, booleans, and many more.

  • How to begin creating the Command Line Search Tool and make programs with Python Sockets

  • And much more…

After reading this book, you will realize that Python Programming is not difficult at all and you don’t need to be rocket scientist to learn it.This revised and thoroughly tested Python guide will get you up to speed and quickly get you to write true programs.

So, what are you waiting for?

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Machine Learning: Master Machine Learning For Business Leaders

$15.99 - $4.77

(as of Jan 20,2020 01:07:51 UTC – Details)

Machine Learning has changed the computing world through its digital interactions because it is a form of artificial intelligence. Machine learning begins with data or observations, like instructions or direct experience, and then looks for patterns in the data that allow the machine to make better decisions based on the examples that have been provided. The main aim of machine learning is to allow the machine to learn automatically without any human assistance or intervention and learn to adjust accordingly.

As a leader a Business Leader Machine Learning is your ticket to advancing your company beyond the competition. Machine learning will help you target your audience, keep your customers happy, and help out money in your bank account.

Inside this book you will learn all related topics like:

  • Machine Learning for your Business
  • Developing the Right Development
  • Data Mining Techniques
  • Business Optimization
  • Machine Learning for Marketing
  • Machine Learning for Finance
  • Day Trading with Machine Learning

And many more…

So grab a copy now and expand your knowledge and expertise with Machine Learning for Business Leaders.

IBM SPSS Modeler Cookbook


(as of Jan 19,2020 23:20:24 UTC – Details)

Over 60 practical recipes to achieve better results using the experts’ methods for data mining


  • Go beyond mere insight and build models than you can deploy in the day to day running of your business
  • Save time and effort while getting more value from your data than ever before
  • Loaded with detailed step-by-step examples that show you exactly how it’s done by the best in the business

In Detail

IBM SPSS Modeler is a data mining workbench that enables you to explore data, identify important relationships that you can leverage, and build predictive models quickly allowing your organization to base its decisions on hard data not hunches or guesswork.

IBM SPSS Modeler Cookbook takes you beyond the basics and shares the tips, the timesavers, and the workarounds that experts use to increase productivity and extract maximum value from data. The authors of this book are among the very best of these exponents, gurus who, in their brilliant and imaginative use of the tool, have pushed back the boundaries of applied analytics. By reading this book, you are learning from practitioners who have helped define the state of the art.

Follow the industry standard data mining process, gaining new skills at each stage, from loading data to integrating results into everyday business practices. Get a handle on the most efficient ways of extracting data from your own sources, preparing it for exploration and modeling. Master the best methods for building models that will perform well in the workplace.

Go beyond the basics and get the full power of your data mining workbench with this practical guide.

What you will learn from this book

  • Use and understand the industry standard CRISP_DM process for data mining.
  • Assemble data simply, quickly, and correctly using the full power of extraction, transformation, and loading (ETL) tools.
  • Control the amount of time you spend organizing and formatting your data.
  • Develop predictive models that stand up to the demands of real-life applications.
  • Take your modeling to the next level beyond default settings and learn the tips that the experts use.
  • Learn why the best model is not always the most accurate one.
  • Master deployment techniques that put your discoveries to work making the most of your business’ most critical resources.
  • Challenge yourself with scripting for ultimate control and automation – it’s easier than you think!


This is a practical cookbook with intermediate-advanced recipes for SPSS Modeler data analysts. It is loaded with step-by-step examples explaining the process followed by the experts.

Who this book is for

If you have had some hands-on experience with IBM SPSS Modeler and now want to go deeper and take more control over your data mining process, this is the guide for you. It is ideal for practitioners who want to break into advanced analytics.

Computer Programming: This Book Includes: Machine Learning for Beginners + Python for Beginners


(as of Jan 19,2020 21:46:15 UTC – Details)

Are you a newbie to Computer Programming? Are you curious to learn why Python is the best way to begin?

Probably you want to start by learning practical techniques that could easily make you become a programmer, developer or simply make you learn how it goes. You probablywould like to learn with examples and images of how the code was written, and afterward an explanation of what is the task and job of each element on the code.

This 2 books in 1 is exactly what you’re looking for !

“Computer Programming” is a complete guide to start learning Python and Machine Learning.

Machine Learning is one of the most exciting developments to come up of computer science since its founding and Python is one of the most used programming language all around the world. The knowledge of Machine Learning and Python is going to give you lots of advantages on your programming technique.

Here’s what you’ll find inside:

  • Introduction to Data Science, AI, Machine Learning and uses of Python;
  • See how Machine Learning is being used by companies like Amazon, Netflix and Google;
  • Benefits of Python and differences between it and other languages;
  • Python basic concepts, as well as Conditional Statements, Loops, Functions, Modules, OOP etc..;
  • And much more…

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Handbook of Relational Learning (Chapman & Hall/CRC Machine Learning & Pattern Recognition)


(as of Jan 19,2020 20:03:52 UTC – Details)

With increased interest in relational learning and the growing importance of machine learning, artificial intelligence, and data mining, inductive logic programming (ILP)—at the boundary between machine learning and logic programming—is on the rise. Authored by a leading researcher in the field, this timely book provides the first comprehensive introduction to be published in over ten years. It uses an accessible approach to present key concepts in ILP and provide an overview of possible applications. The book covers important topics in the field, including probability and statistics, statistical relational learning, experimental design, and combinatorial algorithms.

Data Mining mit SPSS Clementine (Zielsetzung, unterstützte Methoden, Anwendungsbeispiele) (German Edition)


(as of Jan 19,2020 18:13:06 UTC – Details)

Studienarbeit aus dem Jahr 2005 im Fachbereich Informatik – Wirtschaftsinformatik, Note: 1,3, Bayerische Julius-Maximilians-Universität Würzburg (Lehrstuhl für BWL und Wirtschaftsinformatik), Veranstaltung: Hauptseminar Wirtschaftsinformatik, 17 Quellen im Literaturverzeichnis, Sprache: Deutsch, Abstract: Für fast alle Entscheidungen in Unternehmen werden Daten benötigt. Information als Produktionsfaktor gewinnt heute immer mehr an Bedeutung. Während kleine Unternehmen oftmals noch überschaubare Datenbestände verwalten müssen, produzieren und sammeln große internationale Unternehmen mehr Daten innerhalb einer Woche, als ein Mensch in seinem Leben lesen könnte [ADRI96, S. 2]. Dieses Datenwachstum führt dazu, dass Unternehmen „den Wald vor lauter Bäumen nicht mehr sehen“, da diese Datenmengen selbst für große Unternehmen ohne maschinelle Unterstützung einfach nicht mehr handhabbar sind. Immer mehr Daten bedeuten deswegen immer weniger Information. Aus diesem Grund dürfen Daten nicht nur gesammelt werden, sondern müssen konsistent und nutzbar aufbereitet werden. Hier spricht man vom so genannten „data warehousing“ [ADRI96, S. 2; BERR97, S. 3-4]. Data Warehouses sind integrierte Datenbestände, die eine Schicht zwischen den analytischen und operativen Informationssystemen eines Unternehmens bilden [MERT01, S. 131]. Um schließlich einen Nutzen aus diesen Daten generieren zu können müssen die Daten analysiert, verstanden und in entscheidungsunterstützende Informationen umgewandelt werden. Dies ist die Aufgabe von „Data Mining“ [BERR97, S. 3-4].

Focus On: 60 Most Popular Free Software Programmed in Java (programming Language): OSGi, Weka (machine learning), Apache ZooKeeper, Apache Pig, Nxt, Apache … Electric (software), Apache Derby, etc.


(as of Jan 19,2020 16:35:48 UTC – Details)

This carefully crafted ebook is formatted for your eReader with a functional and detailed table of contents. The Focus On books are made out of collections of Wikipedia articles regrouping the most informative and popular articles about a specific subject. The Focus On books are a result of a substantial editorial work of selecting and grouping relevant articles together in order to create a valuable source of information about specific subjects. This book does not contain tables, illustrations or illustration descriptions. Focus On (an imprint of OK Publishing) charges for the convenience service of formatting these e-books. We donate a part of our net income after taxes to the Wikimedia Foundation from the sales of all e-books based on Wikipedia content. You can access the original Wikipedia articles on the internet free of charge.

Data Science from Scratch with Python: A Step By Step Guide for Beginner’s and Faster Way To Learn Python In 7 Days & NLP using Advanced (Including Programming Interview Questions)


(as of Jan 19,2020 14:26:18 UTC – Details)

★★Buy the Paperback Version of this Book and get the Kindle Book version for FREE ★★

Data Science is present in our lives: newspapers talk about viral news, companies look for data scientists, businesses offer us personalized offers based on our customs and we grease the system by offering free personal information from our social networks, Internet searches and even from smart devices to control our daily physical activity.

This book presents the knowledge and technologies that will allow us to participate in this new era of information, governed by Big Data and machine learning, the life of the data is analyzed step by step, showing how to obtain it, store it, process it, visualize it, and draw conclusions from it: that is, show the data analysis as it is: a fascinating area, It requires many hours of careful work. Likewise, the Python programming language is analyzed, the most used in data Science due to the multitude of libraries that it facilitates, but is not limited to the standard, but presents current technologies that, with Python as an interface, will allow scaling the size of the data to the maximum. Therefore, our journey with the data will take us, for example, to know the MongoDB database and the Spark processing environment.

In this book, you will discover:

  • What is a data scientist?

  • What languages should be learned?

  • The three musketeers of Data Science

  • Python introduction

  • Languages do you need to learn for data science

These are some of the topics covered in this book:

  • Machine Learning Algorithms

  • K NN – Nearest Neighbor Method

  • SVC – Support vector machine

  • Mathematics for Data Analysis

  • Working with Threads in Python

  • Working with processes in Python

The book contains detailed examples of how to perform the different tasks in Python; and in addition, for the convenience of the reader of the included fragments, the access of the readers to a repository where they will find the code ready to be executed is facilitated. Also each chapter presents recommended readings to be able to deepen in those aspects that are more interesting. We invite you to immerse yourself in the exciting world of data Science in Python and explore the mysteries of Big Data and machine learning!

Get fit, happy, and stress-free life by ordering your copy right away! also, Don’t miss out on this Data Science from Scratch with Python!

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Blockchain for Medical Research: Accelerating Trust in Healthcare


(as of Jan 19,2020 12:47:12 UTC – Details)

It takes 17 years on average to bring new medical treatments ideas into evidence-based clinical practice. The growing replicability crisis in science further delays these “new miracles.” Blockchain can improve science and accelerate medical research while bringing a new layer of trust to healthcare.

This book is about science, its value to medicine, and how we can use blockchain to improve the quality and impact of both. The book looks at science and medicine from an insider’s perspective and describes the processes, successes, shortcomings and opportunities in an accessible way for a broad audience. It will give a non-technical look at the emerging world of blockchain technology; what it is, where it is useful, and how it can improve science and medicine. It lays out a roadmap for this application to transform how we develop knowledge about health and medicine to improve our lives.

In the first part, Blockchain isn’t Tech, the authors look at blockchain/distributed ledger technology along with critical trade-offs and current explorations of its utility. They give an overview of use cases for the technology across industries, including finance, manufacturing and healthcare, with interviews and insights from leaders across government, academia, and tech/health industry both big and start-up.

In the second part, Science is Easy, the authors look at science as a process and how this drives advancement in medicine. They shed a light on some of science’s shortcomings, including the reproducibility crisis and problems with misaligned incentives (i.e. publish or perish). They apply a breakdown of critical components to the functional steps in the scientific process and outline how the open science movement is looking to improve these, while highlighting the limit of these fixes with current technology, incentives and structure of science.

In the third part, DAO of Science, the authors look at how blockchain applied to Open Science can impact medical research. They examine how this distributed approach can provide better quality science, value-based research and faster medical miracles. Finally, they provide a vision of the future of distributed medical research and give a roadmap of steps to get there.

Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence (Advances in Business Information Systems and Analytics)


(as of Jan 19,2020 11:06:16 UTC – Details)

The development of business intelligence has enhanced the visualization of data to inform and facilitate business management and strategizing. By implementing effective data-driven techniques, this allows for advance reporting tools to cater to company-specific issues and challenges. The Handbook of Research on Advanced Data Mining Techniques and Applications for Business Intelligence is a key resource on the latest advancements in business applications and the use of mining software solutions to achieve optimal decision-making and risk management results. Highlighting innovative studies on data warehousing, business activity monitoring, and text mining, this publication is an ideal reference source for research scholars, management faculty, and practitioners.