Data Science Language

Data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.

Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.

Expand your skills from being a basic data scientist to becoming an expert data scientist ready to solve real-world data-centric issues. Discover two comprehensive manuscripts in one audiobook.

Have you ever felt lost in knowing how your business is actually doing? Were you surprised by events that you didn’t see coming? Did you spend sleepless nights wondering whether or not your company was going to make it? Then Data is for you. This data-driven handbook is the third installment of the Traction Library’s EOS Mastery Series that provides all the tools you need to build an environment of transparency and get better results through clarity and accountability.

This friendly guide teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. This accesible introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python.

It has never been easier for organizations to gather, store, and process data. Use of data science is driven by the rise of big data and social media, the development of high-performance computing, and the emergence of such powerful methods for data analysis and modeling as deep learning. Data science encompasses a set of principles, problem definitions, algorithms, and processes for extracting non-obvious and useful patterns from large datasets.

Data science gets thrown around in the press like it's magic. Major retailers are predicting everything, from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions. Data science is little more than using straightforward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will teach how you how that's done within the familiar environment of a spreadsheet.

Every time we Google something, Facebook someone, or just carry a phone, we create data. Yet, we do not benefit from this wealth of information as much as we should. Andreas Weigend - an advisor to Alibaba, BMW, Hyatt, MasterCard, and Lufthansa, among others - wants to change that. In Data for the People, he proposes six basic data rights that we all need to make better decisions. Big data is here to stay. The time has come to shift the balance of power back to the individual.

There are a lot of benefits to making sure that your network is always safe and secure. And working with the Python language is one of the best ways for you to make sure that we are able to work with some of our own attacks and penetration testing to keep that network safe. Even if you have never worked on hacking in the past, this audiobook is going to give you some of the steps and tips that we need to see the best results with hacking, overall.

Mastering data science doesn’t have to be complicated. Data Science 2020 can help you go from novice to expert in no time at all. To keep up with this growing industry, one has to know all the ins and outs, be able to keep up with the fast-moving innovations, and really understand all the nuances of this field. In this audiobook, you will not only learn what data science is but you will learn all the variables included with it.

Practical Data Science with R lives up to its name. It explains basic principles without the theoretical mumbo-jumbo and jumps right to the real use cases you'll face as you collect, curate, and analyze the data crucial to the success of your business. You'll apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support.

Mastering data science doesn’t have to be complicated. Data Science 2020 can help you go from novice to expert in no time at all. To keep up with this growing industry, one has to know all the ins and outs, be able to keep up with the fast-moving innovations, and really understand all the nuances of this field. In this audiobook, you will not only learn what data science is but you will learn all the variables included with it.

Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases.

R in Action, Second Edition teaches you how to use the R language by presenting examples relevant to scientific, technical, and business developers. Focusing on practical solutions, the book offers a crash course in statistics, including elegant methods for dealing with messy and incomplete data. You'll also master R's extensive graphical capabilities for exploring and presenting data visually. And this expanded second edition includes new chapters on forecasting, data mining, and dynamic report writing.

In this book, you’ll find methods and techniques to organize your data, extract the information, and analyze it. There’s a way to make sure your company is going in the right direction, and this audiobook will reveal the secret behind a successful business.

Go in Action is for any intermediate-level developer who has experience with other programming languages and wants a jump-start in learning Go or a more thorough understanding of the language and its internals. This book provides an intensive, comprehensive, and idiomatic view of Go. It focuses on the specification and implementation of the language, including topics like language syntax, Go's type system, concurrency, channels, and testing.

Today, 91 percent of Python programmers are not quite prepared. This is what the IT companies say, according to a recent survey. Do you know why? The reason is that they have no notions of artificial intelligence. So, future programmers will no longer find work without having knowledge of this particular field that is constantly evolving.

Python programming has become a must-learn skill in the data science domain. It has evolved as the most preferred programming language for data-driven development because it is suitable for many data science tasks and is easy to learn compared to other programming languages. In short, Python is the closest programming language to fit the goal of a beginner and a great starting place.

Would you like to learn to use Python extracting meaningful insight from data to grow your business but you reckon it will be too complex? As a beginner, you will be probably afraid that programming is difficult. Learning data analysis and data mining can take months, and the possibility to give up before mastering them could be high. The best solution is a complete programming manual with hands-on projects and practical exercises. This guide is structured as a course with seven chapters for seven days and studied special exercises to apply what you learned step-by-step.

Data science is the application of a combination of mathematical, statistical, analytical, and programming skills for the collection, organization, and interpretation of data to allow effective and proper management of the business whose data it is. It is a field where one should be trained and practiced. Without proper training and applicative skills, one cannot be as successful as a data scientist. There is a lot to learn about various data science tools and techniques. Getting certified will not only help you hone your skills but also will confirm your future as a data scientist.