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This course lays the foundations for both a theoretical and practical understanding of machine learning and artificial intelligence, utilizing Python as a beginner-friendly introduction and invitation to further study Key Features A crash course in Python programming Interactive, guided practice through a series of machine learning exercises Instant access to PDFs, Python codes, and exercises from the publisher's website at no extra cost Book Description Machine 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 sales. You 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. 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. By the end of this course, you will have a firm grasp on the theoretical foundations of machine learning and artificial intelligence as well as having explored and practiced various real-world applications through Python. The code bundle for this course is availa
This course provides a foundational understanding of machine learning and artificial intelligence through practical Python programming. The book aims to equip beginners with both theoretical knowledge and hands-on experience, covering data analysis, visualization, and statistical models for data science. It emphasizes a practical approach, illustrating concepts with real-world applications and Python code examples. The content is structured to build a firm grasp of ML and AI principles, inviting further study.
The book is presented as a comprehensive introduction to machine learning and artificial intelligence for beginners, with a strong emphasis on practical application using Python. The structure appears designed to build both theoretical understanding and hands-on skills through exercises and code examples. The content covers essential areas like data analysis, visualization, and statistical modeling, aiming to provide a solid foundation for further exploration in the field. Its approach suggests it is well-suited for individuals looking to enter the domain of data science and AI.
Page Count:
448
Publication Date:
2021-03-16
Publisher:
Packt Publishing
ISBN-10:
1801810656
ISBN-13:
9781801810654
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