Python Coding For Kids: The Complete Python Game Programming for Kids by Emenwa Global

This book is designed to help you learn many essential skills you’ll need to make games with Python. You will be able to create games and share them with your friends or even upload them to the app store for the world to play. Are you with me?

This book helps you better understand the big concepts in coding or computer programming and learn Python.
Have you ever thought of controlling an army? You would sit down behind your desk, giving instructions to a computer so that it can perform whatever task you assign it.
Games don’t have to be hard to be fun. You will learn everything about Python, from installing it to using pygame for animation. Overall, a good, sound, and interactive method were used all the way through.

Many people think that programming is only for “PC geeks.” This book is about how to make games with Python. Programming isn’t complicated. If you want to learn about programming, there aren’t many exciting things to know. Most newbie coders don’t need to read other computer books that cover many things that other books don’t cover. Read this book now if you want to learn how to create your own video games. Learn a helpful skill and play games to show for it!
Once you read this book, you will be the cool kid on the block that can code!

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BEGINNERS COURSE ON MACHINE LEARNING: Fundamentals and Practices With Python by Emenwa Global

If you are looking for a machine learning tutorial with Python and Jupyter notebook, it’s your lucky day. You’ll learn how to solve a real-world problem using machine learning and python.
In the US, a machine learning programmer makes an average salary of $166,000! When you have finished this book and implemented the skills you have learned, you will have had enough skills to tackle Machine Learning projects that will either help you obtain your dream job or provide you with the tools you need to use machine learning algorithms to address problems in your business, career, or personal life.
This book uses a project-based learning method to deliver this engaging tutorial with Python.
Create Effective Machine Learning Models to Address Any Issue
By keeping all the boring stuff like math and statistics at the end like a prologue, I ensure that this book will not be boring to those with basic knowledge of Python and statistics or data science. These are very crucial to machine learning on all levels.
The course will teach you how to:
Obtain complete toolkits for machine learning to address the majority of real-world issues.
Recognize the many performance indicators for Regression, classification, and other ML algorithms, including accuracy, and know when to apply them.
Utilize unsupervised Machine Learning (ML) algorithms to comprehend your data, such as hierarchical clustering and k-means clustering.
Develop models using Jupyter (IPython) notebook, and other IDE
Visually and successfully communicate using Matplotlib
Create fresh features to enhance algorithmic forecasts
Decision trees can be used to forecast staff attrition.
And a whole lot more!

Who is this book for?
Anyone who is eager to understand Python’s machine learning algorithms and has a keen interest in how machine learning may be used to solve problems in the real world.
Anyone who wants to learn more than the fundamentals and gain a comprehensive understanding of machine learning algorithms should do so.
Any intermediate to experienced EXCEL users incapable of handling big files
Anyone wishing to begin or advance in a career as a data scientist Anyone wishing to apply machine learning to their field Anyone wishing to communicate their findings in a professional and compelling manner
We’re going to start off with a brief introduction to machine learning, then we’re going to talk about the tools you need, and after that, we’re going to jump straight into the problem we’re going to solve you’ll learn how to build a model that can learn and predict the kind of music people like right in the second chapter.

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BEGINNERS COURSE ON ARTIFICIAL INTELLIGENCE: Fundamentals and Practices With Python by Emenwa Global

The most important thing you must learn here is the best language for Artificial Intelligence as a beginner. There are tons of languages that are designed specifically for AI and machine learning. But the best bet for any beginner is Python.
I say this because it’s the industry standard for machine learning and artificial intelligence. If you get a job in this field, chances are you’re probably using Python to do most of your work. It’s great because you don’t only use it for machine learning, Python can do many other things, and it’s probably one of the more accessible languages to pick up and start using as a beginner.
I also recommend Python because it has the most modules (libraries) and community support for machine learning and artificial intelligence.
I recommend starting with Python. As you get more advanced, you can move into more specific languages, but python is a great one to get started with.
Artificial intelligence uses computers and technology to simulate the human mind’s problem-solving and decision-making abilities. In its most basic form, artificial intelligence is a field that combines computer science and large datasets to solve problems. It also includes the subfields of machine learning and deep learning, which are commonly referenced in the context of artificial intelligence. AI algorithms are used in these areas to develop expert systems that make predictions or classifications based on input data.

In its most basic form, AI (artificial intelligence) refers to systems or robots that mimic human intelligence to execute tasks and can iteratively improve themselves based on the data they collect. AI manifests itself in a variety of ways. Here are a few examples:

AI is used by chatbots to more quickly and effectively comprehend client questions and respond accurately.
AI is used by smart assistants to extract essential data from massive free-text datasets to optimize scheduling.
Based on the watching patterns of consumers, recommendation engines can generate automated recommendations for TV programs.
Rather than focusing on one format or function, AI is far more about the process and the ability for superhuman reasoning and data processing. Although ideas of high-functioning, human-like robots taking over the world conjure up images of AI, the technology is not intended to replace people. Its goal is to vastly improve human skills and contributions. As a result, it is a vital commercial asset.

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