Data Science Engineering

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.

Innovation influences the market and its operators, especially about competition conditions. One of the most significant technological advances relates to the possibility of capturing a huge amount of information and processing them rapidly: two of the main features that make up the phenomenon known as big data. This not only entails the emergence of specialized operators in these activities, but also makes a "data economy" possible.

Explosion of the economic relevance of data is related to: first, technological progress that has drastically reduced the costs of collecting and storing data; second, the advances in analytic techniques that have allowed for more advanced processing to extract greater value from available data. So, more value is extracted from exhausted data. Information generated for one purpose can and should be reused for another one, which means that data moves from primary to secondary uses. Data are more valuable over time.

Do you want to discover all the secrets of Big Data, Deep Learning, and everything in between? Have you ever asked yourself how can artificial intelligences learn from us? Do you want understand how does your smartphone personal assistant can understand you? In this guide, Artus Duval will show you everything you need to know about big data, machine learning, artificial intelligence, and its huge impact on our world; a swell as how to benefit from it 100 percent!

If your business is like most, it is already generating a staggering amount of data on a regular basis. Understanding what this data truly means is key to succeeding in the marketplace these days and if you are looking for a way to give yourself an edge then Data Analytics is the book you have been waiting for. Inside you will find the tools you need in order to take full advantage of all of the data that your business is already generating.

When it comes to choosing, using, and maintaining a database, understanding its internals is essential. But with so many distributed databases and tools available today, it's often difficult to understand what each one offers. With this practical guide, Alex Petrov guides developers through the concepts behind modern database and storage engine internals.

This audiobook teaches you how to build an intelligent system from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems.

If you want to learn about data science and big data, then pay attention....

As a software engineer, you’ll encounter countless programming challenges that initially seem confusing, difficult, or even impossible. Don’t despair! Many of these “new” problems already have well-established solutions. Advanced Algorithms and Data Structures teaches you powerful approaches to a wide range of tricky coding challenges that you can adapt and apply to your own applications. Providing a balanced blend of classic, advanced, and new algorithms, this practical guide upgrades your programming toolbox with new perspectives and hands-on techniques.

Data are no longer just information but a resource that is growing exponentially. There are many powerful ways to store and manipulate data and there are many helpful data science tools that you can use to begin conducting your own analyses. If you are willing to understand more, this audiobook is a crash course on data science.

Python is a powerful programming language, serving a large number of purposes. It is a free and open-source programming language, and it is a very good programming language for beginners, especially for those who are interested to learn computer programming for the very first time. With the help of Python, data manipulation, data visualization, as well as data analysis becomes very simple.

From facial recognition—capable of checking us onto flights or identifying undocumented residents—to automated decision systems that inform everything from who gets loans to who receives bail, each of us moves through a world determined by data-empowered algorithms. But these technologies didn't just appear: they are part of a history that goes back centuries, from the census enshrined in the US Constitution to the birth of eugenics in Victorian Britain to the development of Google search.

Data-Oriented Programming is a one-of-a-kind guide that introduces the data-oriented paradigm. This groundbreaking approach represents data with generic immutable data structures. It simplifies state management, eases concurrency, and does away with the common problems you’ll find in object-oriented code. The book presents powerful new ideas through conversations, code snippets, and diagrams that help you quickly grok what’s great about DOP.

Dark Data explores the many ways in which we can be blind to missing data and how that can lead us to conclusions and actions that are mistaken, dangerous, or even disastrous. Examining a wealth of real-life examples, from the Challenger shuttle explosion to complex financial frauds, Hand gives us a practical taxonomy of the types of dark data that exist and the situations in which they can arise, so that we can learn to recognize and control for them.

Python Data Science is a complete guide on Python for every person who is looking to expand their current or future business, learn the basics of data science, and how Python programming can be used for it. There are so many businesses that are going to benefit when it comes to working with data analysis and seeing this work for some of their needs. It is always a good idea to learn a bit more about this process and how you are able to really use it to learn more about your customers, learn how to beat out your competition, and so much more.

The future of our world is evolving towards an era where interaction with machines form the foundation of most tasks we perform. In light of this, it is important to gain actionable knowledge in machine learning technologies and skills. These skills will be useful in the near future as you maneuver through different career paths. This audiobook introduces you to vast concepts in machine learning that will be important to your career. You will have learned so much about machine learning and the respective python libraries that you will use when building models all the time.

Centralized data warehouses, the long-time de facto standard for housing data for analytics, are rapidly giving way to multi-faceted cloud data platforms. Companies that embrace modern cloud data platforms benefit from an integrated view of their business using all of their data and can take advantage of advanced analytic practices to drive predictions and as yet unimagined data services.

A successful pipeline moves data efficiently, minimizing pauses and blockages between tasks, and keeping processes along the way operational. Apache Airflow provides a single customizable environment for building and managing data pipelines, eliminating the need for a hodgepodge collection of tools, snowflake code, and homegrown processes. Using real-world scenarios and examples, this book teaches you how to simplify and automate data pipelines, reduce operational overhead, and smoothly integrate all the technologies in your stack.

Python Machine Learning is a guide to provide you with all the information required to master machine learning using Python. It will give you deep insight into methods of machine learning, deep learning, big data, data science, and more. Furthermore, it will also teach you concepts of Python and how combining machine learning with Python can result in practical solutions. The audiobook touches upon how these solutions can be applied in various fields including governance, technology, business, cybersecurity, and more.

Algorithms and Data Structures for Massive Datasets reveals a toolbox of new methods that are perfect for handling modern big data applications. You’ll explore the novel data structures and algorithms that underpin Google, Facebook, and other enterprise applications that work with truly massive amounts of data.