Discover easy-to-follow solutions and techniques to help you to implement applied mathematical concepts such as probability, calculus, and equations using Python's numeric and scientific libraries
Key Features
Compute complex mathematical problems using programming logic with the help of step-by-step recipes
Learn how to utilize Python's libraries for computation, mathematical modeling, and statistics
Discover simple yet effective techniques for solving mathematical equations and apply them in real-world statistics
Book Description
Python, one of the world's most popular programming languages, has a number of powerful packages to help you tackle complex mathematical problems in a simple and efficient way. These core capabilities help programmers pave the way for building exciting applications in various domains, such as machine learning and data science, using knowledge in the computational mathematics domain.
The book teaches you how to solve problems faced in a wide variety of mathematical fields, including calculus, probability, statistics and data science, graph theory, optimization, and geometry. You'll start by developing core skills and learning about packages covered in Python's scientific stack, including NumPy, SciPy, and Matplotlib. As you advance, you'll get to grips with more advanced topics of calculus, probability, and networks (graph theory). After you gain a solid understanding of these topics, you'll discover Python's applications in data science and statistics, forecasting, geometry, and optimization. The final chapters will take you through a collection of miscellaneous problems, including working with specific data formats and accelerating code.
By the end of this book, you'll have an arsenal of practical coding solutions that can be used and modified to solve a wide range of practical problems in computational mathematics and data science.
What you will learn
Get familiar with basic packages, tools, and libraries in Python for solving mathematical problems
Explore various techniques that will help you to solve computational mathematical problems
Understand the core concepts of applied mathematics and how you can apply them in computer science
Discover how to choose the most suitable package, tool, or technique to solve a certain problem
Implement basic mathematical plotting, change plot styles, and add labels to the plots using Matplotlib
Get to grips with probability theory with the Bayesian inference and Markov Chain Monte Carlo (MCMC) methods
Who this book is for
This book is for professional programmers and students looking to solve mathematical problems computationally using Python. Advanced mathematics knowledge is not a requirement, but a basic knowledge of mathematics will help you to get the most out of this book. The book assumes familiarity with Python concepts of data structures.
Do you want to master data using python? If yes, then keep reading
Data analysis plays a significant job in numerous parts of your regular day to day existence today. From the second you wake up, you cooperate with information at various levels. A great deal of significant choices are made dependent on information examination. None of the organizations would capacity and run effectively without individuals who realize how to utilize ace this incredible asset. Organizations use information to Understand Their Customer Needs and produce the Best Possible Product or Service.
Python Programming Language is one of the best framework with regards to information examination, and in the event that you are considering starting your own business some time or another or as of now have one, this is certainly a device you should comprehend and utilize.
Data Scientist is the most requested job of the 21st century and Python is the most popular programming language of the 21st century. The average salary of a Data Scientist is around 120 thousand dollars per year and the average salary of a Pythton Developer is around 100 thousand dollars. So it's pretty obvious that anyone have skills in both Data Science and Python will be in great demand in industry.
You needn't bother with an exhausting and costly reading material. This book is the best one for every readers.
This book covers:
- Introduction to Python and data analysis
- Python basics
- Python history
- Installing Python
- Data analysis with Python
- NumPy for numerical data processing
- Data visualization with Python
- Machine learning with Python
And much more
Be it Data Processing, Data Analytics, Data Modeling, Data Visualization, Data Predictive, Machine Learning, or taking the photo of Blackhole: Python is everywhere and it is the most powerful programming language of 21st century. Beloved by the data scientists and new generation developers, Pyhton will eat the word
Описание: Unlock the programming skills you need to prepare for a lucrative career in Data Science with this comprehensive introduction to Python programming for data analytics
Are you completely new to programming and want to learn how to code, but don't know where to begin? Are you looking to upgrade your data wrangling skills to future-proof your career and break into Data Science and Analytics?
If you answered yes to any of the questions above, then keep reading...
Data analysis has become a huge industry with tons of career potential and will remain relevant far into the foreseeable future.
With the exponential growth and explosion of new data and the focus on using data to improve customer experiences and carry out research, data analysts will be needed to process and make sense of large amounts of information, with Python being the language of choice because of its versatility.
In this guide, you're going to be shown everything you need to break into the world of Data Analysis with Python. Filled with tutorials for powerful libraries and practical, hands-on exercises, you're going to learn how to aggregate, munge, analyze and visualize data in Python.
Here's a sample of what you're going to discover in Python Data Analytics
Why Python is the perfect language to learn if you want to break into Big Data and data analytics
Core statistical models and computation methods you need to know about as a budding data analyst
How to master the CSV library for reading, writing and handling tabular data
Using the Xlrd library to extract data from Microsoft Excel files
How to convert text to speech using the powerful Win32.com library
How to use the NumPy library to carry out fundamental and basic scientific and technical computing
How to use the SciPy library to carry out advanced scientific and highly technical computing
Surefire ways to manipulate the easy-to-use data structures of the Pandas framework for high-performance data analysis
How to plot complex data, create figures and visualize data using the Python Matplotlib library
...and tons more
If you're completely new to programming and have never written a single line of code, but want to get started, this guide is perfect for as a crash guide to getting up to speed with programming in general.
Whether you're a programmer looking to switch into an exciting new field with lots of potential for the future, or a regular data analyst looking to acquire the skills needed to remain relevant in a fast-changing world, this guide will teach you how to master powerful libraries used in the real-world by experienced data scientists.
Автор: Smart Gary Название: Practical Python Programming for IoT ISBN: 1838982469 ISBN-13(EAN): 9781838982461 Издательство: Неизвестно Рейтинг: Цена: 9562.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Leverage Python and Raspberry Pi to create complex IoT applications capable of creating and detecting movement and measuring distance, light, and a host of other environmental conditions
Key features
Learn the fundamentals of electronics and how to integrate them with a Raspberry Pi
Understand how to build RESTful APIs, WebSocket APIs, and MQTT-based applications
Explore alternative approaches to structuring IoT applications with Python
Book Description
The age of connected devices is here, be it fitness bands or smart homes. It's now more important than ever to understand how hardware components interact with the internet to collect and analyze user data. The Internet of Things (IoT), combined with the popular open source language Python, can be used to build powerful and intelligent IoT systems with intuitive interfaces.
This book consists of three parts, with the first focusing on the "Internet" component of IoT. You'll get to grips with end-to-end IoT app development to control an LED over the internet, before learning how to build RESTful APIs, WebSocket APIs, and MQTT services in Python. The second part delves into the fundamentals behind electronics and GPIO interfacing. As you progress to the last part, you'll focus on the "Things" aspect of IoT, where you will learn how to connect and control a range of electronic sensors and actuators using Python. You'll also explore a variety of topics, such as motor control, ultrasonic sensors, and temperature measurement. Finally, you'll get up to speed with advanced IoT programming techniques in Python, integrate with IoT visualization and automation platforms, and build a comprehensive IoT project.
By the end of this book, you'll be well-versed with IoT development and have the knowledge you need to build sophisticated IoT systems using Python.
What you will learn
Understand electronic interfacing with Raspberry Pi from scratch
Gain knowledge of building sensor and actuator electronic circuits
Structure your code in Python using Async IO, pub/sub models, and more
Automate real-world IoT projects using sensor and actuator integration
Integrate electronics with ThingSpeak and IFTTT to enable automation
Build and use RESTful APIs, WebSockets, and MQTT with sensors and actuators
Set up a Raspberry Pi and Python development environment for IoT projects
Who this book is for
This IoT Python book is for application developers, IoT professionals, or anyone interested in building IoT applications using the Python programming language. It will also be particularly helpful for mid to senior-level software engineers who are experienced in desktop, web, and mobile development, but have little to no experience of electronics, physical computing, and IoT.
Автор: Ilya Shpigor Название: Practical Video Game Bots ISBN: 1484237358 ISBN-13(EAN): 9781484237359 Издательство: Springer Рейтинг: Цена: 6288.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: pacote do Courseware consiste em duas publicacoes, VeriSMTM - Foundation Courseware e VeriSM - Foundation Study Guide. Este material de treinamento abrange o plano de estudos para a qualificacao da Fundacao VeriSM . O treinamento pode ser entregue em dois dias. Este material didatico e credenciado para preparar o aluno para a certificacao da VeriSM Foundation. O VeriSM Foundation consiste em duas partes: VeriSM Essentials e VeriSM Plus, cada uma cobrindo um dia de treinamento.Os alunos que ja possuem um certificado de Gerenciamento de Servicos (TI) podem se beneficiar do conhecimento que ja possuem. Eles sao o publico-alvo de apenas um treinamento do VeriSM Plus. Ao serem aprovados no exame VeriSM Plus, recebem o certificado VeriSM Foundation.Provedores de treinamento que desejam oferecer um treinamento de um dia sobre principios de gerenciamento de servicos podem decidir oferecer apenas o treinamento VeriSM Essentials. Os alunos que forem aprovados no exame VeriSM Essentials receberao o certificado VeriSM Essentials. Se eles passarem no exame VeriSM Plus mais tarde, receberao automaticamente o certificado VeriSM Foundation.O "courseware" abrange os seguintes topicos:A organizacao do servico (Essentials)Cultura de servico (Essentials)Pessoas e estrutura organizacional (Essentials)O modelo VeriSM (ambos)Praticas Progressivas (Plus)Tecnologias Inovadoras (Plus)O VeriSM e uma abordagem holistica e orientada aos negocios para o Gerenciamento de Servicos, que ajuda a entender o panorama crescente das melhores praticas e como integra-las para oferecer valor ao consumidor.E uma evolucao no pensamento em Gerenciamento de Servicos e oferece uma abordagem atualizada, incluindo as mais recentes praticas e desenvolvimentos tecnologicos, para ajudar as organizacoes a transformar seus negocios para a nova realidade da era digital.O VeriSM e um gerenciamento orientado a valor, evolutivo, responsivo e integrado.VeriSM e uma marca registrada e propriedade da IFDC, a Fundacao Internacional de Competencias Digitais.
Автор: Manohar Swamynathan Название: Mastering Machine Learning with Python in Six Steps ISBN: 1484249461 ISBN-13(EAN): 9781484249468 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Explore fundamental to advanced Python 3 topics in six steps, all designed to make you a worthy practitioner. This updated version’s approach is based on the “six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away and presents each topic in two parts: theoretical concepts and practical implementation using suitable Python 3 packages.You’ll start with the fundamentals of Python 3 programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as exploratory analysis, feature dimension reduction, regressions, time series forecasting and their efficient implementation in Scikit-learn are covered as well. You’ll also learn commonly used model diagnostic and tuning techniques. These include optimal probability cutoff point for class creation, variance, bias, bagging, boosting, ensemble voting, grid search, random search, Bayesian optimization, and the noise reduction technique for IoT data. Finally, you’ll review advanced text mining techniques, recommender systems, neural networks, deep learning, reinforcement learning techniques and their implementation. All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage.What You'll LearnUnderstand machine learning development and frameworksAssess model diagnosis and tuning in machine learningExamine text mining, natuarl language processing (NLP), and recommender systemsReview reinforcement learning and CNNWho This Book Is ForPython developers, data engineers, and machine learning engineers looking to expand their knowledge or career into machine learning area.
Автор: Subasi, Abdulhamit Название: Practical Machine Learning For Data Analysis Using Python ISBN: 0128213795 ISBN-13(EAN): 9780128213797 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems.
Are you looking for a crash course that will help you learn Python? Do you want to master data science using Python? If yes, then keep reading
Python is one of the most popular programming languages in the word in 2020 and specially for data science. Every day people use it to do cool things like Automation, they use it in Artificial Intelligence, Machine Learning, as well as Building Applications and Websites like Instagram and Dropbox. YouTube, Pinterest, and SurveyMonkey are all built on Python. So if you are looking for a trendy job, like data scientist, Python is for you.
This is a Python guide with 2 Books in 1:
Python crash course
Python for data analysis
Python has seen an explosion in popularity in recent years, driven by several aspects that make it an incredibly versatile and intuitive language.
Moreover, data analysis plays a significant job in numerous parts of your regular day to day existence today. Organizations use information to Understand Their Customer Needs and produce the Best Possible Product or Service. Python Programming Language is one of the best framework with regards to information examination.
Data Scientist is the most requested job of the 21st century and Python is the most popular programming language of the 21st century. So it's pretty obvious that anyone have skills in both Data Science and Python will be in great demand in industry.
You needn't bother with an exhausting and costly reading material. This guide is the best one for every readers.
This guide covers:
The world of data science technologies
Application of machine learning
Data scientist: the sexiest job in the 21st century
Learning Python from scratch
Data analysis with Python
NumPy for numerical data processing
Data visualization with Python
Projects on Python
And much more
Despite its simplicity, Python is also sturdy and robust enough to carry out complex scientific and mathematical tasks. Python has been designed with features that drastically simplify the visualization and analysis of data, and Python is also the go-to choice for the creation of machine learning models and artificial intelligence.
Be it machine learning, data analytics, data processing, web development, enterprise software development or taking the photo of Blackhole: Python is everywhere. Beloved by the data scientists and new generation developers, Pyhton will eat the word
Are you looking for a crash course that will help you learn Python? Do you want to master data science using Python? If yes, then keep reading
Python is one of the most popular programming languages in the word in 2020 and specially for data science. Every day people use it to do cool things like Automation, they use it in Artificial Intelligence, Machine Learning, as well as Building Applications and Websites like Instagram and Dropbox. YouTube, Pinterest, and SurveyMonkey are all built on Python. So if you are looking for a trendy job, like data scientist, Python is for you.
This is a Python guide with 2 Books in 1:
Python crash course
Python for data analysis
Python has seen an explosion in popularity in recent years, driven by several aspects that make it an incredibly versatile and intuitive language.
Moreover, data analysis plays a significant job in numerous parts of your regular day to day existence today. Organizations use information to Understand Their Customer Needs and produce the Best Possible Product or Service. Python Programming Language is one of the best framework with regards to information examination.
Data Scientist is the most requested job of the 21st century and Python is the most popular programming language of the 21st century. So it's pretty obvious that anyone have skills in both Data Science and Python will be in great demand in industry.
You needn't bother with an exhausting and costly reading material. This guide is the best one for every readers.
This guide covers:
The world of data science technologies
Application of machine learning
Data scientist: the sexiest job in the 21st century
Learning Python from scratch
Data analysis with Python
NumPy for numerical data processing
Data visualization with Python
Projects on Python
And much more
Despite its simplicity, Python is also sturdy and robust enough to carry out complex scientific and mathematical tasks. Python has been designed with features that drastically simplify the visualization and analysis of data, and Python is also the go-to choice for the creation of machine learning models and artificial intelligence.
Be it machine learning, data analytics, data processing, web development, enterprise software development or taking the photo of Blackhole: Python is everywhere. Beloved by the data scientists and new generation developers, Pyhton will eat the word
Описание: If you want to learn Python in one week (or less) and learn it well, with useful applications to Data Analysis, Machine Learning and Data Science, then keep reading.
Python is one of the most beloved programming languages in any circle of programmers. Software engineers, hackers, and Data Scientists alike are in love with the versatility that Python has to offer. Besides, the Object-Oriented feature of Python coupled with its flexibility is also one of the major attractions for this language.
That's the reason why Python is a perfect fit with Data Analysis, Machine Learning and Data Science.
Data is the future. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations.
The goal of this 4-in-1 bundle is simple: explaining everything you need to know to Master Python. With a special emphasis on the main steps that are needed to correctly implement Data Analysis and Machine Learning algorithms,
In manuscript one, Python for Beginners, you will learn:
How to install Python
What are the different Python Data Types and Variables
Basic Operators of Python Language
Data Structures and Functions
Conditional and Loops in Python
And Much More
In manuscript two, Python Advanced Guide, you will master:
Object-Oriented Programming (OOP), Inheritance and Polymorphism
Essential Programming Tools
Exception Handling
Working with Files
And Much More
In manuscript three, Python for Data Analysis, you will learn:
What Data Analysis is all about and why businesses are investing in this sector
The 5 steps of a Data Analysis
The 7 Python libraries that make Python one of the best choices for Data Analysis
Pandas, Jupyter and PyTorch
And Much More
In manuscript four, Applications to Data Science, you will understand:
How Data Visualization and Matplotlib can help you to understand the data you are working with.
Neural Networks
Decision Trees
What industries are using data to improve their business with 14 real-world applications
And So Much More
Where most books about Python programming are theoretical and have few or little practical examples, this book provides lots of simple, step-by-step examples and illustrations that are used to underline key concepts and help improve your understanding.
Furthermore, topics are carefully selected to give you broad exposure to Python, while not overwhelming you with too much information. Also, the outputs of ALL the examples are provided immediately so you do not have to wait till you have access to your computer to test the examples.
Even if you have never coded before, this is the perfect guide because it breaks down complex concepts into simple steps and in a concise and simple way that fits well with beginners. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them, and the most important real-world applications.
Would you like to know more?Scroll Up and Click the BUY NOW Button to Get Your Copy
Описание: If you want to learn Python in one week (or less) and learn it well, with useful applications to Data Analysis, Machine Learning and Data Science, then keep reading.
Python is one of the most beloved programming languages in any circle of programmers. Software engineers, hackers, and Data Scientists alike are in love with the versatility that Python has to offer. Besides, the Object-Oriented feature of Python coupled with its flexibility is also one of the major attractions for this language.
That's the reason why Python is a perfect fit with Data Analysis, Machine Learning and Data Science.
Data is the future. The world of technology as we know it is evolving towards an open-source platform where people share ideas freely. This is seen as the first step towards the decentralization of ideas and eliminating unnecessary monopolies. Therefore, the data, tools, and techniques used in the analysis are easily available for anyone to interpret data sets and get relevant explanations.
The goal of this 4-in-1 bundle is simple: explaining everything you need to know to Master Python. With a special emphasis on the main steps that are needed to correctly implement Data Analysis and Machine Learning algorithms,
In manuscript one, Python for Beginners, you will learn:
How to install Python
What are the different Python Data Types and Variables
Basic Operators of Python Language
Data Structures and Functions
Conditional and Loops in Python
And Much More
In manuscript two, Python Advanced Guide, you will master:
Object-Oriented Programming (OOP), Inheritance and Polymorphism
Essential Programming Tools
Exception Handling
Working with Files
And Much More
In manuscript three, Python for Data Analysis, you will learn:
What Data Analysis is all about and why businesses are investing in this sector
The 5 steps of a Data Analysis
The 7 Python libraries that make Python one of the best choices for Data Analysis
Pandas, Jupyter and PyTorch
And Much More
In manuscript four, Applications to Data Science, you will understand:
How Data Visualization and Matplotlib can help you to understand the data you are working with.
Neural Networks
Decision Trees
What industries are using data to improve their business with 14 real-world applications
And So Much More
Where most books about Python programming are theoretical and have few or little practical examples, this book provides lots of simple, step-by-step examples and illustrations that are used to underline key concepts and help improve your understanding.
Furthermore, topics are carefully selected to give you broad exposure to Python, while not overwhelming you with too much information. Also, the outputs of ALL the examples are provided immediately so you do not have to wait till you have access to your computer to test the examples.
Even if you have never coded before, this is the perfect guide because it breaks down complex concepts into simple steps and in a concise and simple way that fits well with beginners. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them, and the most important real-world applications.
Would you like to know more?Scroll Up and Click the BUY NOW Button to Get Your Copy
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