If you want to learn more about Machine Learning and Data Science or how to master them with Python quickly and easily, then keep reading.
Data Science and Machine Learning are one of the biggest buzzwords in the business world nowadays. Many businesses know the importance of collecting information, but as they can collect so much data in a short period, the real question is: "what is the next step?"
Data Science includes all the different steps that you take with the data: collecting and cleaning them, analyzing them, applying Machine Learning algorithms and models, and then presenting your findings from the analysis with some good Data Visualizations.
Machines and automation represent a huge part of our daily life. They are becoming part of our experience, and existence. Artificial Intelligence is currently one of the most thriving fields any programmer would wish to delve into, and for a good reason: this is the future
Simply put, Machine Learning is about teaching machines to think and make decisions as we would. The difference between the way machines learn and the way we do is that while for the most part we learn from experiences, machines learn from data.
In book one, PYTHON MACHINE LEARNING, you will learn:
What is Machine Learning and how it is applied in real-world situations
Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence
Machine learning training models, Regression techniques and Linear Regression in Python
How to use Lists and Modules in Python
The 12 essential libraries for Machine Learning in Python
Artificial Neural Networks
And Much More
In book two, PYTHON DATA SCIENCE, you will learn:
What Data Science is all about and why so many companies are using it to give them a competitive edge.
Why Python and how to use it to implement Data Science
The main Data Structures & Object-Oriented Programming, Functions and Modules in Python with practical codes and exercises
The 7 most important algorithms and models in Data Science
Data Aggregation, Group Operations, Databases and Data in the Cloud
9 important Data Mining techniques in Data Science
And So Much More
Where most books only focus on how collecting and cleaning the data, this book goes further, providing guidance on how to perform a proper analysis in order to extract precious information that may be vital for a business.
Don't miss the opportunity to master the key points of Machine Learning technology and understand how researchers are breaking the boundaries of Data Science to mimic human intelligence in machines.
Even if some Machine Learning concepts and algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way. Understanding Machine Learning and Data Science is easier than it looks. You just need the right guidance. And this bundle provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the techniques to manipulate and process datasets, the principles of Python programming, and its most important real-world applications.
Would You Like To Know More?Scroll Up and Click the BUY NOW Button to Get Your Copy
If you want to learn more about Machine Learning and Data Science or how to master them with Python quickly and easily, then keep reading.
Data Science and Machine Learning are one of the biggest buzzwords in the business world nowadays. Many businesses know the importance of collecting information, but as they can collect so much data in a short period, the real question is: "what is the next step?"
Data Science includes all the different steps that you take with the data: collecting and cleaning them, analyzing them, applying Machine Learning algorithms and models, and then presenting your findings from the analysis with some good Data Visualizations.
Machines and automation represent a huge part of our daily life. They are becoming part of our experience, and existence. Artificial Intelligence is currently one of the most thriving fields any programmer would wish to delve into, and for a good reason: this is the future
Simply put, Machine Learning is about teaching machines to think and make decisions as we would. The difference between the way machines learn and the way we do is that while for the most part we learn from experiences, machines learn from data.
In book one, PYTHON MACHINE LEARNING, you will learn:
What is Machine Learning and how it is applied in real-world situations
Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence
Machine learning training models, Regression techniques and Linear Regression in Python
How to use Lists and Modules in Python
The 12 essential libraries for Machine Learning in Python
Artificial Neural Networks
And Much More
In book two, PYTHON DATA SCIENCE, you will learn:
What Data Science is all about and why so many companies are using it to give them a competitive edge.
Why Python and how to use it to implement Data Science
The main Data Structures & Object-Oriented Programming, Functions and Modules in Python with practical codes and exercises
The 7 most important algorithms and models in Data Science
Data Aggregation, Group Operations, Databases and Data in the Cloud
9 important Data Mining techniques in Data Science
And So Much More
Where most books only focus on how collecting and cleaning the data, this book goes further, providing guidance on how to perform a proper analysis in order to extract precious information that may be vital for a business.
Don't miss the opportunity to master the key points of Machine Learning technology and understand how researchers are breaking the boundaries of Data Science to mimic human intelligence in machines.
Even if some Machine Learning concepts and algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way. Understanding Machine Learning and Data Science is easier than it looks. You just need the right guidance. And this bundle provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the techniques to manipulate and process datasets, the principles of Python programming, and its most important real-world applications.
Would You Like To Know More?Scroll Up and Click the BUY NOW Button to Get Your Copy
Today, we live in the era of Artificial Intelligence. Self-driving cars, customized product recommendations, real-time pricing, speech and facial recognition are just a few examples proving this truth. Also, think about medical diagnostics or automation of mundane and repetitive labor tasks; all these highlight the fact that we live in interesting times. From research topics to projects and applications in different stages of production, there is a lot going on in the world of Machine Learning.
Machines and automation represent a huge part of our daily life. They are becoming part of our experience and existence. This is Machine Learning. Artificial Intelligence is currently one of the most thriving fields any programmer would wish to delve into, and for a good reason: this is the future
Simply put, Machine Learning is about teaching machines to think and make decisions as we would. The difference between the way machines learn and the way we do is that while for the most part we learn from experiences, machines learn from data.
Starting from scratch, Python Machine Learning explains how this happens, how machines build their experience and compounding knowledge. Data forms the core of Machine Learning because within data lie truths whose depths exceed our imagination. The computations machines can perform on data are incredible, beyond anything a human brain could do. Once we introduce data to a machine learning model, we must create an environment where we update the data stream frequently. This builds the machine's learning ability. The more data Machine Learning models are exposed to, the easier it is for these models to expand their potential.
Some of the topics that we will discuss inside include:
What is Machine Learning and how it is applied in real-world situations
Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence
Supervised learning, unsupervised learning, and semi-supervised learning
The place of Regression techniques in Machine Learning, including Linear Regression in Python
Machine learning training models
How to use Lists and Modules in Python
The 12 essential libraries for Machine Learning in Python
What is the Tensorflow library
Artificial Neural Networks
And Much More
While most books only focus on widespread details without going deeper into the different models and techniques, Python Machine Learning explains how to master the concepts of Machine Learning technology and helps you to understand how researchers are breaking the boundaries of Data Science to mimic human intelligence in machines using various Machine Learning algorithms.
Even if some concepts of Machine Learning algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way.
Would You Like To Know More?
Scroll up and click the BUY NOWbutton to get your copy now
Автор: Park Andrew Название: Python Machine Learning: A Complete Guide for Beginners on Machine Learning and Deep Learning ISBN: 1914167538 ISBN-13(EAN): 9781914167539 Издательство: Неизвестно Рейтинг: Цена: 22030.00 T Наличие на складе: Нет в наличии. Описание: If you want to learn how to design and master different Machine Learning algorithms quickly and easily, then keep reading.
Today, we live in the era of Artificial Intelligence. Self-driving cars, customized product recommendations, real-time pricing, speech and facial recognition are just a few examples proving this truth. Also, think about medical diagnostics or automation of mundane and repetitive labor tasks; all these highlight the fact that we live in interesting times. From research topics to projects and applications in different stages of production, there is a lot going on in the world of Machine Learning.
Machines and automation represent a huge part of our daily life. They are becoming part of our experience and existence. This is Machine Learning. Artificial Intelligence is currently one of the most thriving fields any programmer would wish to delve into, and for a good reason: this is the future
Simply put, Machine Learning is about teaching machines to think and make decisions as we would. The difference between the way machines learn and the way we do is that while for the most part we learn from experiences, machines learn from data.
Starting from scratch, Python Machine Learning explains how this happens, how machines build their experience and compounding knowledge. Data forms the core of Machine Learning because within data lie truths whose depths exceed our imagination. The computations machines can perform on data are incredible, beyond anything a human brain could do. Once we introduce data to a machine learning model, we must create an environment where we update the data stream frequently. This builds the machine's learning ability. The more data Machine Learning models are exposed to, the easier it is for these models to expand their potential.
Some of the topics that we will discuss inside include:
What is Machine Learning and how it is applied in real-world situations
Understanding the differences between Machine Learning, Deep Learning, and Artificial Intelligence
Supervised learning, unsupervised learning, and semi-supervised learning
The place of Regression techniques in Machine Learning, including Linear Regression in Python
Machine learning training models
How to use Lists and Modules in Python
The 12 essential libraries for Machine Learning in Python
What is the Tensorflow library
Artificial Neural Networks
And Much More
While most books only focus on widespread details without going deeper into the different models and techniques, Python Machine Learning explains how to master the concepts of Machine Learning technology and helps you to understand how researchers are breaking the boundaries of Data Science to mimic human intelligence in machines using various Machine Learning algorithms.
Even if some concepts of Machine Learning algorithms can appear complex to most computer programming beginners, this book takes the time to explain them in a simple and concise way.
Would You Like To Know More?
Scroll up and click the BUY NOWbutton to get your copy now
Data Science is one of the biggest buzzwords in the business world nowadays. Many businesses know the importance of collecting information, but as they can collect so much data in a short period, the real question is: "what is the next step?"
Data Science includes all the different steps that you take with the data: collecting and cleaning them if they come from more than one source, analyzing them, applying Machine Learning algorithms and models, and then presenting your findings from the analysis with some good Data Visualizations.
And this is what you will learn in Python Data Science.
You will learn about the main steps that are needed to correctly implement Data Science techniques and the algorithms to help you sort through the data and see some amazing results. Some of the topics that we will discuss inside include:
What data science is all about and why so many companies are using it to give them a competitive edge.
Why Python and how to use it to implement Data Science
What is the intersection between Machine Learning and Data Science and how to combine them
The main Data Structures & Object-Oriented Python, with practical codes and exercises to use Python
Functions and Modules in Python
The 7 most important algorithms and models in Data Science
Data Aggregation and Group Operations
9 important Data Mining techniques in Data Science
Interaction with databases and data in the cloud
And Much More
Where most books only focus on how collecting and cleaning the data, this book goes further, providing guidance on how to perform a proper analysis in order to extract precious information that may be vital for a business. Don't miss the opportunity to learn more about these topics.
Even if you have never implemented Data Science techniques, learning them is easier than it looks. You just need the right guidance. And Python Data Science provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn, the techniques to manipulate and process datasets, the principles of Python programming, and its most important real-world applications.
Would You Like To Know More?Scroll Up And Click The BUY NOW Button To Get Your Copy Now
Everyone talks about data today. You have probably come across the term "data" more times than you can remember in one day. Data as a concept is so wide. One thing that is true about data is that it can be used to tell a story. The story could be anything from explaining an event to predicting the future.
Data is the future. Businesses, governments, organizations, criminals-everyone needs data for some reason. Entities are investing in different data approaches to help them understand their current situation, and use it to prepare for the unknown. 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.
With Python for Data Analysis you will learn about the main steps that are needed to correctly implement Data Analysis and the procedures to help you extract the right insights from the right data. Some of the topics that we will discuss inside include:
What Data Analysis is all about and why businesses are investing in this sector
The 5 steps of a Data Analysis
Pandas, Jupyter and PyTorch
The 7 Python libraries that make Python one of the best choices for Data Analysis
Neural Network
How Data Visualization and Matplotlib can help you to understand the data you are working with.
Some of the main industries that are using data to improve their business with 14 real-world applications
And Much More
While most books focus on how to implement advanced predictive models, this book takes the time to explain the basic concepts and all the necessary steps to correctly implement Data Analysis, including Data Visualization and providing practical examples and simple coding scripts. Don't miss the opportunity to learn more about these topics.
Even if you never used Data Analysis, learning it is easier than it looks, you just need the right guidance. This practical guide provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them in Python, 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
Everyone talks about data today. You have probably come across the term "data" more times than you can remember in one day. Data as a concept is so wide. One thing that is true about data is that it can be used to tell a story. The story could be anything from explaining an event to predicting the future.
Data is the future. Businesses, governments, organizations, criminals-everyone needs data for some reason. Entities are investing in different data approaches to help them understand their current situation, and use it to prepare for the unknown. 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.
With Python for Data Analysis you will learn about the main steps that are needed to correctly implement Data Analysis and the procedures to help you extract the right insights from the right data. Some of the topics that we will discuss inside include:
What Data Analysis is all about and why businesses are investing in this sector
The 5 steps of a Data Analysis
Pandas, Jupyter and PyTorch
The 7 Python libraries that make Python one of the best choices for Data Analysis
Neural Network
How Data Visualization and Matplotlib can help you to understand the data you are working with.
Some of the main industries that are using data to improve their business with 14 real-world applications
And Much More
While most books focus on how to implement advanced predictive models, this book takes the time to explain the basic concepts and all the necessary steps to correctly implement Data Analysis, including Data Visualization and providing practical examples and simple coding scripts. Don't miss the opportunity to learn more about these topics.
Even if you never used Data Analysis, learning it is easier than it looks, you just need the right guidance. This practical guide provides all the knowledge you need in a simple and practical way. Regardless of your previous experience, you will learn the steps of Data Analysis, how to implement them in Python, 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
Python is a powerful programming language that can be used for the development of various types of applications. It is an Object-Oriented Programming language and it is interpreted rather than being compiled.
Python is considered to be among 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 some of the major attractions for this language. Programmers are now developing a wide range of mobile as well as web applications that we enjoy on an everyday basis.
This book explains every single detail that you must know to start using Python. From Python installation to Object-Oriented Programming, from the definition of Data Types and Variables to a practical application on Decision Trees.
You will learn everything that you need to know to start programming with Python. Some of the topics that we will discuss inside include:
Python installation
Python Data Types
Python Variables
Basic Operators of Python Language
Data Structures
Learning about Functions
Conditional and Loops in Python
Object-Oriented Programming (OOP)
Inheritance and Polymorphism
Essential Programming Tools
Working with Files
Exception Handling
An application to Decision Trees
And Much More
Where most books about Python programming are theoretical and have few or little practical examples, Python for Beginners provides lots of simple, step-by-step examples and illustrations that are used to underline key conceptsand 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, unlike the majority of books, 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, Python for Beginners 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, so that you can easily master the Python language.
Would you like to become a Python geek?
Scroll to the top of the page and click the BUY NOW button to get your copy now
Would you like to become a Python geek? Or do you want to learn more about the fascinating world of Machine Learning an Data Science? Well, the solution is right in front of you
With this bundle in your hands, you'll go from beginner to pro in no time. These books and guides are specifically designed for people that have little or no prior knowledge about Python Programming.
Everything inside is designed to be step-by-step, so you can have an easier time understanding the concepts around it.
This comprehensive bundle contains everything you'll need to know to successfully implement Data Science techniques and Machine Learning algorithms through Python. From basic tutorials and exercises to expert coding techniques.
In book one, PYTHON FOR BEGINNERS, you will learn:
How to install Python
What are the different Python Data Types, Variables and Basic Operators
Data Structures, Functions and Files
Conditional and Loops in Python
Object-Oriented Programming (OOP), Inheritance and Polymorphism
Essential Programming Tools and Exception Handling
And Much More
In book two, PYTHON FOR DATA ANALYSIS, you will:
Learn the Fundamentals of Data Analysis and why Businesses are Investing in this Sector
Master the 5 steps of a Proper Data Analysis
Know what are the 7 Python libraries that make Python one of the best choices for Data Analysis
Learn how Data Visualization and Matplotlib can help You to Understand the Data you are Working with
Learn about some of the Main Industries that are Using Data to Improve their Business with 14 real-world Applications
And Much More
In book three, PYTHON MACHINE LEARNING, you will understand:
What are the Basics of Machine Learning and how it is Applied in real-world Situations
What is the Difference between Machine Learning, Deep Learning, and Artificial Intelligence
How to Implement Machine Learning Training Models, Regression Techniques and Linear Regression in Python
How to use Lists and Modules in Python
What are the 12 Essential Libraries for Machine Learning in Python
How to Correctly use Artificial Neural Networks
And Much More
And in book four, PYTHON DATA SCIENCE, you will discover:
What Data Science is all about and why so many Companies are Using it to get a Competitive Edge.
The main Data Structures & Object-Oriented Programming, Functions and Modules in Python with Practical Codes and Exercises
The 7 Most Important Algorithms and Models in Data Science
Data Aggregation, Group Operations, Databases and Data in the Cloud
9 important Data Mining techniques in Data Science
And So Much More
It doesn't matter if you are a beginner, or you never have coded before. This guide will slowly ease you into the world of Data Science. While most of the other similar books put the focus on theory and complicated concepts, this one is designed specifically for beginners.
Furthermore, topics are carefully selected to give you broad exposure, while not overwhelming you with too much information. Also, unlike the majority of books, 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.
Ready to Master Python, Machine Learning and Data Science?Scroll Up and Click the BUY NOWButton to Get Your Copy
Автор: Campbell, Andrew,Park, Robert Название: The Growth Gamble ISBN: 1473658462 ISBN-13(EAN): 9781473658462 Издательство: Little Brown Рейтинг: Цена: 20240.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Too many companies kiss a lot of frogs in search of a prince. The Growth Gamble shows you how to spot princes at a distance.More and more corporations are experiencing a "growth gap" when the natural growth of their core businesses is not enough. Nearly every company tries to create new legs for its mature portfolio, yet as many as 99 percent of companies fail to create successful new growth platforms. Based on extensive new research The Growth Gamble is a major new book on the toughest challenge in management - finding, getting into and growing new businesses. Its startling conclusions will help you to "Stop Kissing Frogs " and enter only the most promising and profitable sectors for you company's strengths. Most importantly, the book will arm you with practical tools to help your company make the right decision based on a Traffic Lights Toolkit - a powerful screening and strategic thinking tool that helps managers identify real opportunities and learn to "Only Go On Green." With some startling "red light" conclusions, this exciting new book gives alternatives, equipping practitioners with the tools which help them to make the right decisions and identify good prospects without the trial and error.
Автор: Hempstead Andrew Название: Moon Banff National Park: Hike - Camp - See Wildlife ISBN: 1640498826 ISBN-13(EAN): 9781640498822 Издательство: Little Brown Рейтинг: Цена: 10110.00 T Наличие на складе: Поставка под заказ. Описание: Women of war examines the FANY as a case study of gender modernity using newspapers, memoirs, diaries, letters interviews, photographs and poetry. While these New Women challenged the limits of convention in terms of behaviour, dress and role, they were simulataneously deepy conservative, upholding imperialist, unionist and anti-feminist values. -- .
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