ISBN
9781789538243
Get up and running with Artificial Intelligence using 8 smart and exciting AI applications :
This book demonstrates AI projects in Python covering modern techniques that make up the world of Artificial Intelligence. You will come across a variety of real-world projects on classifying data, text processing techniques, deep learning and neural networks
Author/Authors: Eckroth, Joshua
Pages: 162 | Published Date: 43312
Category: Data
ISBN
9781785289668
Leverage the computational power of Python with more than 60 recipes that arm you with the required skills to make informed business decisions :
Leverage the computational power of Python with more than 60 recipes that arm you with the required skills to make informed business decisions About This Book • Want to minimize risk and optimize profits of your business? Learn to create efficient analytical reports with ease using this highly practical, easy-to-follow guide • Learn to apply Python for business intelligence tasksâ€â€preparing, exploring, analyzing, visualizing and reportingâ€â€in order to make more informed business decisions using data at hand • Learn to explore and analyze business data, and build business intelligence dashboards with the help of various insightful recipes Who This Book Is For This book is intended for data analysts, managers, and executives with a basic knowledge of Python, who now want to use Python for their BI tasks. If you have a good knowledge and understanding of BI applications and have a “working†system in place, this book will enhance your toolbox. What You Will Learn • Install Anaconda, MongoDB, and everything you need to get started with your data analysis • Prepare data for analysis by querying cleaning and standardizing data • Explore your data by creating a Pandas data frame from MongoDB • Gain powerful insights, both statistical and predictive, to make informed business decisions • Visualize your data by building dashboards and generating reports • Create a complete data processing and business intelligence system In Detail The amount of data produced by businesses and devices is going nowhere but up. In this scenario, the major advantage of Python is that it's a general-purpose language and gives you a lot of flexibility in data structures. Python is an excellent tool for more specialized analysis tasks, and is powered with related libraries to process data streams, to visualize datasets, and to carry out scientific calculations. Using Python for business intelligence (BI) can help you solve tricky problems in one go. Rather than spending day after day scouring Internet forums for “how-to†information, here you’ll find more than 60 recipes that take you through the entire process of creating actionable intelligence from your raw data, no matter what shape or form it’s in. Within the first 30 minutes of opening this book, you’ll learn how to use the latest in Python and NoSQL databases to glean insights from data just waiting to be exploited. We’ll begin with a quick-fire introduction to Python for BI and show you what problems Python solves. From there, we move on to working with a predefined data set to extract data as per business requirements, using the Pandas library and MongoDB as our storage engine. Next, we will analyze data and perform transformations for BI with Python. Through this, you will gather insightful data that will help you make informed decisions for your business. The final part of the book will show you the most important task of BIâ€â€visualizing data by building stunning dashboards using Matplotlib, PyTables, and iPython Notebook. Style and approach This is a step-by-step guide to help you prepare, explore, analyze and report data, written in a conversational tone to make it easy to grasp. Whether you’re new to BI or are looking for a better way to work, you’ll find the knowledge and skills here to get your job done efficiently.
Author/Authors: Dempsey, Robert
Pages: 202 | Published Date: 42360
Category: Data
ISBN
9781783553365
Learn how to apply powerful data analysis techniques with popular open source Python modules :
This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.
Author/Authors: Idris, Ivan
Pages: 348 | Published Date: 41940
Category: Data
ISBN
9781787127920
Learn how to apply powerful data analysis techniques with popular open source Python modules :
This book is for programmers, scientists, and engineers who have the knowledge of Python and know the basics of data science. It is for those who wish to learn different data analysis methods using Python 3.5 and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.
Author/Authors: Fandango, Armando
Pages: 330 | Published Date: 42821
Category: Data
ISBN
9781785283857
Over 140 practical recipes to help you make sense of your data with ease and build production-ready data apps :
This book is hands-on and low on theory. You should have better than beginner Python knowledge and have some knowledge of linear algebra, calculus, machine learning and statistics. Ideally, you would have read Python Data Analysis, but this is not a requirement. I also recommend the following books: • Building Machine Learning Systems with Python by Willi Richert and Luis Pedro Coelho, 2013 • Learning NumPy Array by Ivan Idris, 2014 • Learning scikit-learn: Machine Learning in Python by Guillermo Moncecchi, 2013 • Learning SciPy for Numerical and Scientific Computing by Francisco J. Blanco-Silva, 2013 • Matplotlib for Python Developers by Sandro Tosi, 2009 • NumPy Beginner's Guide - Third Edition by Ivan Idris, 2015 • NumPy Cookbook – Second Edition by Ivan Idris, 2015 • Parallel Programming with Python by Jan Palach, 2014 • Python Data Visualization Cookbook by Igor Milovanović, 2013 • Python for Finance by Yuxing Yan, 2014 • Python Text Processing with NLTK 2.0 Cookbook by Jacob Perkins, 2010
Author/Authors: Idris, Ivan
Pages: 462 | Published Date: 42573
Category: Data
ISBN
9781784393663
Over 60 practical recipes to help you explore Python and its robust data science capabilities :
This book is intended for all levels of data science professionals, both students and practitioners from novice to experts. Different recipes in the chapters cater to the needs of different audiences. Novice readers can spend some time in getting themselves acquainted with data science in the first five chapters. Experts can refer to the later chapters to refer/understand how advanced techniques are implemented using Python. The book covers just enough mathematics and provides the necessary references for computer programmers who wish to understand data science. People from a non-Python background can effectively use this book. The first chapter of the book introduces Python as a programming language for data science. It will be helpful if you have some prior basic programming experience. The book is mostly self-contained and introduces data science to a new reader and can help him become an expert in this trade.
Author/Authors: Subramanian, Gopi
Pages: 438 | Published Date: 42324
Category: Data
ISBN
9781785287893
Become an efficient data science practitioner by thoroughly understanding the key concepts of Python :
If you are an aspiring data scientist and you have at least a working knowledge of data analysis and Python, this book will get you started in data science. Data analysts with experience of R or MATLAB will also find the book to be a comprehensive reference to enhance their data manipulation and machine learning skills.
Author/Authors: Boschetti, Alberto | Massaron, Luca
Pages: 258 | Published Date: 42124
Category: Data
ISBN
9781789531893
A practitioner’s guide covering essential data science principles, tools, and techniques, 3rd Edition :
Python Data Science Essentials, Third Edition provides modern insight in setting up and performing data science operations effectively using the latest python tools and libraries. It builds faster governance on the most essential tasks such as data munging and pre-processing, along with all the techniques you require.
Author/Authors: Boschetti, Alberto | Massaron, Luca
Pages: 472 | Published Date: 43371
Category: Data
ISBN
9781782163374
Over 60 recipes that will enable you to learn how to create attractive visualizations using Python's most popular libraries :
This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the code in this book is explained almost line by line. You don't need maths for this book, every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic.
Author/Authors: Milovanović, Igor
Pages: 280 | Published Date: 41603
Category: Data
ISBN
9781784394943
Over 70 recipes to get you started with popular Python libraries based on the principal concepts of data visualization :
Python Data Visualization Cookbook, Second Edition is for developers and data scientists who already use Python and want to learn how to create visualizations of their data in a practical way. If you have heard about data visualization but don't know where to start, this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data. You will need to know some general programming concepts, and any kind of programming experience will be helpful. However, the code in this book is explained almost line by line. You don't need math for this book; every concept that is introduced is thoroughly explained in plain English, and references are available for further interest in the topic.
Author/Authors: Milovanović, Igor | Foures, Dimitry | Vettigli, Giuseppe
Pages: 302 | Published Date: 42338
Category: Data
ISBN
9781786460660
Take your machine learning skills to the next level by mastering Deep Learning concepts and algorithms using Python. :
This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.
Author/Authors: Zocca, Valentino | Spacagna, Gianmario | Slater, Daniel | Roelants, Peter
Pages: 406 | Published Date: 42853
Category: Data
ISBN
9781787122253
Solve different problems in modelling deep neural networks using Python, Tensorflow, and Keras with this practical guide :
This book is intended for machine learning professionals who are looking to use deep learning algorithms to create real-world applications using Python. Thorough understanding of the machine learning concepts and Python libraries such as NumPy, SciPy and scikit-learn is expected. Additionally, basic knowledge in linear algebra and calculus is desired.
Author/Authors: Bakker, Indra den
Pages: 330 | Published Date: 43035
Category: Data
