Search query: machine learning python

Product: PYTHON MACHINE LEARNING: THE ABSOLUTE BEGINNER’S GUIDE FOR UNDERSTAND NEURAL NETWORK, ARTIFICIAL INTELLIGENT, DEEP LEARNING AND MASTERING THE FUNDAMENTALS OF ML WITH PYTHON
Description: Are you new to machine learning and looking to eventually launch a career in Python?

Do you want to learn how to do machine learning with Python but you have problems getting started?

Machine learning is a subject that has quickly become popular in a wide range of domains such as Data Science, Artificial intelligence among others. The use of machine learning in these domains offers incredible opportunities. If you are just starting your career, this could just be the best decision you make.

Have you been thinking of learning Python as your first programming language? Do you have data that you have generated and do not know where to start analyzing them? Are you interested in digesting your big data into meaningful information that will inform decision makers?

Well, you have come to the right place!

So many people think that they need to have expertise in math and programming for them to use Python at all. Trust me,

you need zero-experience!

All you need is interest and a strong motivation to learn all these things. You may be thinking to yourself “But why Python?” Well, there are so many reasons why Python is the best programming language to start with.

In this book, you’ll learn all the important topics that you need to know for you to implement machine learning with Python. Such topics you will meet include:

An introduction and principles behind machine learning
How to download, install Python, and get the best package for machine learning in Python.
You’ll load a dataset and understand its structure using data visualization and summaries.
Getting dirty with Python
The algorithms that constitute to machine learning
The core foundations of data science, neural networks and deep learning
The libraries you can never avoid
And much more!!

Python is a powerful interpreted language

. Unlike other languages such as R, Python is a complete language and platform where you can apply both research and development production. Still, there are many modules and libraries which you can select from and generate different ways to perform each task.

Are you ready to take upon the challenge? Good!

Press the buy now button and get you copy of this book.
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Product: Machine Learning with Python: The Ultimate Guide for Absolute Beginners with Steps to Implement Artificial Neural Networks with Real Examples (Useful Python Tools eg. Anaconda, Jupiter Notebook)
Description: Do you want to learn how machine learning and neural networks work quickly and simply? Do you want to know how to build a machine learning model, and you have no programming skills? Do you want to get started with learning data science?

This book is going to guide you to the basics and the principles behind machine learning. Machine learning is an active research domain and includes several different approaches.

This book is going to help you understand the various methods of machine learning and neural networks.

It will guide you through the steps you need to build a machine learning model.

Machine learning implies programming. This book will teach you Python programming. This book does not require any pre-programming skills. It will help to get you started in Python programming, as well as how to use Python libraries to analyze data and apply machine learning.

Overall, this book is a go-to guide for getting started in machine learning modeling using Python programming. Once you get through the book, you will be able to develop your machine learning models using Python.

Through this book, you will learn:

• Principles of machine learning

• Types of machine learning: supervised, unsupervised, semi-supervised, and reinforcement learning

• Advantages of each type of machine learning

• Principle and types of neural networks

• Steps to develop and fit artificial neural network model

• Getting started and installing Python

• Tools and platforms for Python programming

• How to use pandas, NumPy and matplotlib Python libraries

• How to develop a simple linear and logistic machine learning model

• How to build and train a multi-layer artificial neural network two ways: from scratch and using the Python libraries

Even if you don’t have any background in machine learning and Python programming, this book will give you the tools to develop machine learning models.

Would you like to know more?

Scroll to the top of the page and select the BUY NOW button!
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Product: Machine Learning: 2 Books in 1: Python Machine Learning and Data Science. A Comprehensive Guide for Beginners to Master Deep Learning, Artificial Intelligence ... Python. (The Intelligent Data Scientist)
Description: Master The World Of Machine Learning And Data Science With This Comprehensive 2-in-1 bundle

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.
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Product: Python Machine Learning: A Complete Guide for Beginners on Machine Learning and Deep Learning with Python (Data Science Book 3)
Description: 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.
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Product: Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2, 3rd Edition
Description: Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning.

Key Features

Third edition of the bestselling, widely acclaimed Python machine learning book
Clear and intuitive explanations take you deep into the theory and practice of Python machine learning
Fully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practices

Book Description

Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.

Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.

Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.

This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.

What you will learn

Master the frameworks, models, and techniques that enable machines to 'learn' from data
Use scikit-learn for machine learning and TensorFlow for deep learning
Apply machine learning to image classification, sentiment analysis, intelligent web applications, and more
Build and train neural networks, GANs, and other models
Discover best practices for evaluating and tuning models
Predict continuous target outcomes using regression analysis
Dig deeper into textual and social media data using sentiment analysis

Who This Book Is For

If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.

Table of Contents

Giving Computers the Ability to Learn from Data
Training Simple ML Algorithms for Classification
ML Classifiers Using scikit-learn
Building Good Training Datasets - Data Preprocessing
Compressing Data via Dimensionality Reduction
Best Practices for Model Evaluation and Hyperparameter Tuning
Combining Different Models for Ensemble Learning
Applying ML to Sentiment Analysis
Embedding a ML Model into a Web Application
Predicting Continuous Target Variables with Regression Analysis
Working with Unlabeled Data - Clustering Analysis
Implementing Multilayer Artificial Neural Netw
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Product: The Hundred-Page Machine Learning Book
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Product: Python Machine Learning By Example: Implement machine learning algorithms and techniques to build intelligent systems, 2nd Edition
Brand: Packt Publishing
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Product: PYTHON PROGRAMMING: 2 book in 1: A complete guide from beginner to intermediate on python machine learning, data science, tools (Computer Programming 5)
Description: Master the world of Computer Programming with Python and Machine Learning with this comprehensive 2-in-1 Bundle

Are you interested in programming? Do you want to uncover the secrets of python data analysis, data science, and machine learning? Looking for the best ways to familiarize yourself with this amazing language, no matter your level of experience? Then this is the bundle for you!

The truth is: Programming is a complex process that needs eminent practice along with a lot of patience. A lot of beginners who stumble upon programming quickly change their mind after dealing with few programs practically. Dealing with a complex programming language at the beginning may be overwhelming and will result in discouragement.

Inside this incredible 2 book collection, you will discover how you can get started with the world of python. Containing a wealth of practical strategies, tips and tricks, and easy-to-understand explanations, now it’s never been easier to begin programming with the world of python.

In book one, PYTHON PROGRAMMING FOR BEGINNERS you will learn about:

● How to install it in your system?

● How to deal with variables and data types?

● What are the basic operations of Python?

● How can we give interactivity to Python programs?

● What is object-oriented programming?

● How to create user-made functions?

● How to use structures in Python?

In book two, PYTHON PROGRAMMING FOR INTERMEDIATE you will learn:

● A good comparison between all the available python versions

● A brief explanation about Functional programming

● A chapter about different operators available

● A section in the book explaining about iterators, generators, and interactions

● A sample project that helps you to understand Project management

● A brief introduction to machine learning and famous machine learning libraries

● Explanation about Loops and classes in detail

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, so that you can easily master the Python language.

Become an Expert of Python and Data Analysis today!

Scroll up and Click the

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Button to Get Your Copy!
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Product: Deep Learning with Python
Brand: Manning Publications
Care instruction: Keep away from fire
It can be used as a gift
It is made up of premium quality material.
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Product: Data Science from Scratch: First Principles with Python
Brand: O'Reilly Media
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Product: Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Brand: O'Reilly Media
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Product: Machine Learning with Python Cookbook: Practical Solutions from Preprocessing to Deep Learning
Brand: O'Reilly Media
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Product: Hands–On Machine Learning with Scikit–Learn and TensorFlow
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Product: Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
Brand: O'Reilly Media
O Reilly Media
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Product: Introduction to Machine Learning with Python: A Guide for Data Scientists
Brand: O'Reilly Media
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Product: Foundations of Deep Reinforcement Learning: Theory and Practice in Python (Addison-Wesley Data & Analytics Series)
Brand: Addison-Wesley Professional
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Product: Python Machine Learning - Second Edition: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow
Brand: Packt Publishing
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