Expert Python Programming, 4th EditionThis new edition of Expert Python Programming provides you with a thorough understanding of the process of building and maintaining Python apps. Complete with best practices, useful tools, and standards implemented by professional Python developers, this fourth edition has been extensively updated. Become familiar with the latest Python improvements, syntax elements, and interesting tools to boost your development efficiency.
The initial few chapters will allow experienced programmers coming from different languages to transition to the Python ecosystem. You will explore common software design patterns and various programming methodologies, such as event-driven programming, concurrency, and metaprogramming. You will also go through complex code examples and try to solve meaningful problems by bridging Python with C and C++, writing extensions that benefit from the strengths of multiple languages. Finally, you will understand the complete lifetime of any application after it goes liv ...
Advanced Forecasting with PythonCover all the machine learning techniques relevant for forecasting problems, ranging from univariate and multivariate time series to supervised learning, to state-of-the-art deep forecasting models such as LSTMs, recurrent neural networks, Facebook's open-source Prophet model, and Amazon's DeepAR model.
Rather than focus on a specific set of models, this book presents an exhaustive overview of all the techniques relevant to practitioners of forecasting. It begins by explaining the different categories of models that are relevant for forecasting in a high-level language. Next, it covers univariate and multivariate time series models followed by advanced machine learning and deep learning models. It concludes with reflections on model selection such as benchmark scores vs. understandability of models vs. compute time, and automated retraining and updating of models.
Each of the models presented in this book is covered in depth, with an intuitive simple explanation of the model, a m ...
Advanced Analytics with Transact-SQLLearn about business intelligence (BI) features in T-SQL and how they can help you with data science and analytics efforts without the need to bring in other languages such as R and Python. This book shows you how to compute statistical measures using your existing skills in T-SQL. You will learn how to calculate descriptive statistics, including centers, spreads, skewness, and kurtosis of distributions. You will also learn to find associations between pairs of variables, including calculating linear regression formulas and confidence levels with definite integration.
No analysis is good without data quality. Advanced Analytics with Transact-SQL introduces data quality issues and shows you how to check for completeness and accuracy, and measure improvements in data quality over time. The book also explains how to optimize queries involving temporal data, such as when you search for overlapping intervals. More advanced time-oriented information in the book includes hazard and surviva ...
Just Enough RIf your job involves working with data in any manner, you cannot afford to ignore the R revolution! If your domain is called data analysis, analytics, informatics, data science, reporting, business intelligence, data management, big data, or visualization, you just have to learn R as this programming language is a game-changing sledgehammer.
However, if you have looked at a standard text on R or read some of the online discussions, you might feel that there is a steep learning curve of six months or more to grok the language. I will debunk this myth through my book by focusing on practical essentials instead of theory.
If you have programmed in some language in the past (whether that language be SAS, SPSS, C, C++, C#, Java, Python, Perl, Visual Basic, Ruby, Scala, shell scripts, or plain old SQL), even if you are rusty, this book will get you up and running with R in a single day, writing programs for data analysis and visualization. ...
Financial Theory with PythonNowadays, finance, mathematics, and programming are intrinsically linked. This book provides the relevant foundations of each discipline to give you the major tools you need to get started in the world of computational finance.
Using an approach where mathematical concepts provide the common background against which financial ideas and programming techniques are learned, this practical guide teaches you the basics of financial economics. Written by the best-selling author of Python for Finance, Yves Hilpisch, Financial Theory with Python explains financial, mathematical, and Python programming concepts in an integrative manner so that the interdisciplinary concepts reinforce each other.
Draw upon mathematics to learn the foundations of financial theory and Python programming; Learn about financial theory, financial data modeling, and the use of Python for computational finance; Leverage simple economic models to better understand basic notions of finance and Python programming co ...
Communicating with DataData is a fantastic raw resource for powering change in an organization, but all too often the people working in those organizations don't have the necessary skills to communicate with data effectively. With this practical book, subject matter experts will learn ways to develop strong, persuasive points when presenting data to different groups in their organizations.
Author Carl Allchin shows anyone how to find data sources and develop data analytics, and teaches those with more data expertise how to visualize data to convey findings to key business leaders more effectively. Once both your business and data experts possess the skills to work with data and interpret its significance, you can deal with questions and challenges in departments across your organization.
Learn the fundamental data skills required to work with data; Use data visualization to influence change in your organization; Learn how to apply data techniques to effectively work with data end to end; Understand how ...
Deep Learning with Python, 2nd EditionDeep Learning with Python has taught thousands of readers how to put the full capabilities of deep learning into action. This extensively revised second edition introduces deep learning using Python and Keras, and is loaded with insights for both novice and experienced ML practitioners. You'll learn practical techniques that are easy to apply in the real world, and important theory for perfecting neural networks.
Recent innovations in deep learning unlock exciting new software capabilities like automated language translation, image recognition, and more. Deep learning is quickly becoming essential knowledge for every software developer, and modern tools like Keras and TensorFlow put it within your reach - even if you have no background in mathematics or data science. This book shows you how to get started.
Deep Learning with Python, Second Edition introduces the field of deep learning using Python and the powerful Keras library. In this revised and expanded new edition, Keras cre ...
C and Python ApplicationsSolve problems by embedding Python code in a C programs, SQL methods, Python sockets. This book uses rudimentary mathematics and basic programming to create practical Python applications for embedding.
You'll start with an introduction to C and Python, assuming a fundamental understanding of what programming is. You will also review the basics of the database management language, SQL. You will learn how to use SQL from a C program and from a Python program. C and Python have different programming strengths, and you will learn how to write a Python program embedded within a C program to profit from the strength of each, in one program. Finally, you will explore how socket programs enable two computers to communicate with each other. Here the book covers basic server-client, basic threaded, and basic chat programs. ...
Object-Oriented PythonObject-Oriented Programming (OOP) is a paradigm that combines data and code into cohesive units, allowing you to think differently about computational problems and solve them in a highly reusable way. Aimed at intermediate-level programmers, Object-Oriented Python is a hands-on tutorial that goes deep into the core tenets of OOP, showing you how to use encapsulation, polymorphism, and inheritance to write games and apps using Python.
The book begins by demonstrating key problems inherent in procedural programming, then guides you through the basics of creating classes and objects in Python. You'll build on this groundwork by developing buttons, text fields, and other GUI elements that are standard in event-driven environments. You'll also use many real-world code examples and two pygame-based packages to help turn theory into practice, enabling you to easily write interactive games and applications complete with GUI widgets, animations, multiple scenes, and reusable game logic. In t ...
How to Think Like a Computer ScientistHow to Think Like a Computer Scientist: Learning with Python - is an introduction to computer science using the Python programming language. It covers the basics of computer programming, including variables and values, functions, conditionals and control flow, program development and debugging. Later chapters cover basic algorithms and data structures. ...