Python Machine Learning for BeginnersMachine Learning (ML) and Artificial Intelligence (AI) are here to stay. Yes, that's right. Based on a significant amount of data and evidence, it's obvious that ML and AI are here to stay.Consider any industry today. The practical applications of ML are really driving business results. Whether it's healthcare, e-commerce, government, transportation, social media sites, financial services, manufacturing, oil and gas, marketing and salesYou name it. The list goes on. There's no doubt that ML is going to play a decisive role in every domain in the future.But what does a Machine Learning professional do?A Machine Learning specialist develops intelligent algorithms that learn from data and also adapt to the data quickly. Then, these high-end algorithms make accurate predictions. Python Machine Learning for Beginners presents you with a hands-on approach to learn ML fast.How Is This Book Different?AI Publishing strongly believes in learning by doing methodology. With this in mind, we have crafted this book with care. You will find that the emphasis on the theoretical aspects of machine learning is equal to the emphasis on the practical aspects of the subject matter.You'll learn about data analysis and visualization in great detail in the first half of the book. Then, in the second half, you'll learn about machine learning and statistical models for data science.Each chapter presents you with the theoretical framework behind the different data science and machine learning techniques, and practical examples illustrate the working of these techniques.When you buy this book, your learning journey becomes so much easier. The reason is you get instant access to all the related learning material presented with this book--references, PDFs, Python codes, and exercises--on the publisher's website. All this material is available to you at no extra cost. You can download the ML datasets used in this book at runtime, or you can access them via the Resources/Datasets folder.You'll also find the short course on Python programming in the second chapter immensely useful, especially if you are new to Python. Since this book gives you access to all the Python codes and datasets, you only need access to a computer with the internet to get started. The topics covered include: Introduction and Environment Setup Python Crash Course Python NumPy Library for Data Analysis Introduction to Pandas Library for Data Analysis Data Visualization via Matplotlib, Seaborn, and Pandas Libraries Solving Regression Problems in ML Using Sklearn Library Solving Classification Problems in ML Using Sklearn Library Data Clustering with ML Using Sklearn Library Deep Learning with Python TensorFlow 2.0 Dimensionality Reduction with PCA and LDA Using Sklearn Click the BUY NOW button to start your Machine Learning journey.

Python机器学习的初学者机器学习（ML）和人工智能（AI）在这里停留。是的，这是对的。基于大量的数据和证据，很明显，ML和AI在这里停留。考虑一下今天的任何行业。ML的实际应用正在真正推动商业成果。无论是医疗保健、电子商务、政府、交通、社交媒体网站、金融服务、制造业、石油和天然气、营销和销售，你都可以说出来。这个名单还在继续。毫无疑问，ML将在未来的每个领域发挥决定性的作用。但是，机器学习专家是做什么的？机器学习专家开发智能算法，从数据中学习，也能快速适应数据。然后，这些高端算法做出准确的预测。Python Machine Learning for Beginners》为你提供了一个快速学习ML的实践方法。这本书有什么不同？AI Publishing坚信在实践中学习的方法。考虑到这一点，我们精心制作了这本书。你会发现，对机器学习的理论方面的强调与对实践方面的强调是同等的。在本书的前半部分，你会非常详细地了解到数据分析和可视化。然后，在后半部分，你将学习机器学习和数据科学的统计模型。每一章都向你介绍不同的数据科学和机器学习技术背后的理论框架，并以实际例子说明这些技术的工作原理。当你购买这本书时，你的学习之路变得非常容易。原因是你可以在出版商的网站上即时获得与本书有关的所有学习材料--参考文献、PDF、Python代码和练习。所有这些材料对你来说都是免费的。你可以在运行时下载本书中使用的ML数据集，也可以通过Resources/Datasets文件夹访问它们。你还会发现第二章中关于Python编程的简短课程非常有用，特别是如果你是Python的新手。由于本书让你可以访问所有的Python代码和数据集，你只需要访问一台有互联网的计算机就可以开始了。涉及的主题包括 介绍和环境设置 Python速成班 用于数据分析的Python NumPy库介绍 用于数据分析的Pandas库 通过Matplotlib、Seaborn和Pandas库实现数据可视化 使用Sklearn库解决ML中的回归问题 使用Sklearn库解决ML中的分类问题 使用Sklearn库进行数据聚类 使用Python进行深度学习 TensorFlow 2.0 使用Sklearn进行PCA和LDA降维 点击现在购买按钮，开始你的机器学习之旅。