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Quantum Machine Learning with Python
Quantum Machine Learning with Python

Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particles. It also examines Quantum machine learning, which can help solve some of the most challenging problems in forecasting, financial modeling, genomics, cybersecurity, supply chain logistics, cryptography among others. You'll start by reviewing the fundamental concepts of Quantum Computing, such as Dirac Notations, Qubits, and Bell state, followed by postulates and mathematical foundations of Quantum Computing. Once the foundation base is set, you'll delve deep into Quantum based algorithms including Quantum Fourier transform, phase estimation, and HHL (Harrow-Hassidim-Lloyd) among others. You'll then be introduced to Quantum machine learning and Quantum deep learning-based algorithms, ...
Generative AI with Python and TensorFlow 2
Generative AI with Python and TensorFlow 2

In recent years, generative artificial intelligence has been instrumental in the creation of lifelike data (images, speech, video, music, and text) from scratch. In this book you will unpack how these powerful models are created from relatively simple building blocks, and how you might adapt these models to your own use cases. You will begin by setting up clean containerized environments for Python and getting to grips with the fundamentals of deep neural networks, learning about core concepts like the perceptron, activation functions, backpropagation, and how they all tie together. Once you have covered the basics, you will explore deep generative models in depth, including OpenAI's GPT-series of news generators, networks for style transfer and deepfakes, and synergy with reinforcement learning. As you progress, you will focus on abstractions where useful, and understand the "nuts and bolts" of how the models are composed in code, underpinned by detailed architecture diagrams. T ...
Python Notes for Professionals
Python Notes for Professionals

The Python Notes for Professionals book is compiled from Stack Overflow Documentation, the content is written by the beautiful people at Stack Overflow. ...
Python and R for the Modern Data Scientist
Python and R for the Modern Data Scientist

Success in data science depends on the flexible and appropriate use of tools. That includes Python and R, two of the foundational programming languages in the field. This book guides data scientists from the Python and R communities along the path to becoming bilingual. By recognizing the strengths of both languages, you'll discover new ways to accomplish data science tasks and expand your skill set. Authors Rick Scavetta and Boyan Angelov explain the parallel structures of these languages and highlight where each one excels, whether it's their linguistic features or the powers of their open source ecosystems. You'll learn how to use Python and R together in real-world settings and broaden your job opportunities as a bilingual data scientist. Learn Python and R from the perspective of your current language; Understand the strengths and weaknesses of each language; Identify use cases where one language is better suited than the other; Understand the modern open source ecosystem av ...
Robust Python
Robust Python

Does it seem like your Python projects are getting bigger and bigger? Are you feeling the pain as your codebase expands and gets tougher to debug and maintain? Python is an easy language to learn and use, but that also means systems can quickly grow beyond comprehension. Thankfully, Python has features to help developers overcome maintainability woes. In this practical book, author Patrick Viafore shows you how to use Python's type system to the max. You'll look at user-defined types, such as classes and enums, and Python's type hinting system. You'll also learn how to make Python extensible and how to use a comprehensive testing strategy as a safety net. With these tips and techniques, you'll write clearer and more maintainable code. Learn why types are essential in modern development ecosystems; Understand how type choices such as classes, dictionaries, and enums reflect specific intents; Make Python extensible for the future without adding bloat; Use popular Python tools to in ...
Learn Quantum Computing with Python and Q#
Learn Quantum Computing with Python and Q#

Learn Quantum Computing with Python and Q# demystifies quantum computing. Using Python and the new quantum programming language Q#, you'll build your own quantum simulator and apply quantum programming techniques to real-world examples including cryptography and chemical analysis. Quantum computers present a radical leap in speed and computing power. Improved scientific simulations and new frontiers in cryptography that are impossible with classical computing may soon be in reach. Microsoft's Quantum Development Kit and the Q# language give you the tools to experiment with quantum computing without knowing advanced math or theoretical physics. Learn Quantum Computing with Python and Q# introduces quantum computing from a practical perspective. Use Python to build your own quantum simulator and take advantage of Microsoft's open source tools to fine-tune quantum algorithms. The authors explain complex math and theory through stories, visuals, and games. You'll learn to apply quant ...
Python for You and Me
Python for You and Me

This is a simple open book to learn Python programming language, it is for the programmers who are new to Python. Python is an interpreted, high-level and general-purpose programming language. Python consistently ranks as one of the most popular programming languages. Large organizations that use Python include Wikipedia, Google, Yahoo, CERN, NASA, Dropbox, IBM, Mozilla, Facebook, Amazon, Instagram, Spotify, Reddit, ... ...
Advanced Forecasting with Python
Advanced Forecasting with Python

Cover 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 ...
Full Stack Python Security
Full Stack Python Security

Full Stack Python Security: Cryptography, TLS, and attack resistance teaches you everything you'll need to build secure Python web applications. As you work through the insightful code snippets and engaging examples, you'll put security standards, best practices, and more into action. Along the way, you'll get exposure to important libraries and tools in the Python ecosystem. Security is a full-stack concern, encompassing user interfaces, APIs, web servers, network infrastructure, and everything in between. Master the powerful libraries, frameworks, and tools in the Python ecosystem and you can protect your systems top to bottom. Packed with realistic examples, lucid illustrations, and working code, this book shows you exactly how to secure Python-based web applications. Full Stack Python Security: Cryptography, TLS, and attack resistance teaches you everything you need to secure Python and Django-based web apps. In it, seasoned security pro Dennis Byrne demystifies complex secur ...
Financial Theory with Python
Financial Theory with Python

Nowadays, 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 ...
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