Big Data Machine Learning | 大数据机器学习 from edX

How to process big data is an ongoing challenge facing machine learning. Currently, the problem of machine learning processing large-scale data is very common. How to propose a machine learning algorithm that meets the needs of big data processing is a hot research topic in the era of big data. The "Big Data Machine Learning" course is a basic theoretical course for senior undergraduates and graduate students in the Department of Information Science. Its purpose is to train students to comprehensively understand the theoretical basis of big data machine learning and firmly master the methods and solutions of big data machine learning. Ability to solve practical problems. This course mainly studies machine learning and deep learning methods, aiming to realize the application of big data machine learning. The main contents of this course include:

Basic theory of statistical learning
.Basic methods of machine learning
Deep learning theories and methods

An ongoing challenge for machine learning is how to deal with big data. At present, the problem of machine learning dealing with large-scale data is widespread. How to propose a machine learning algorithm to meet the needs of big data processing is a hot research topic in the big data era. The course " Big Data Machine Learning" is a basic theory course for senior undergraduates and postgraduates in information science department. Its purpose is to cultivate students' comprehensive ability to understand the theoretical basis of Big Data Machine Learning, master the methods of Big Data Machine Learning firmly, and solve practical problems. This course focuses on the methodsof machine learning and deep learning, and aims to realize the application of big data machine learning. The main contents of the course include:

The basic theories of statistical learning
The basic methods of machine learning
The theories and methods of deep learning

What's inside

Learning objectives

Basic concepts of big data machine learning
Big data machine learning technology and principles
.machine learning and deep learning algorithms

Basic concepts of big data machine learning
Principles and techniques of big data machine learning
Algorithms of machine learning and deep learning

Basic concepts of big data machine learning
Big data machine learning technology and principles
.machine learning and deep learning algorithms
Basic concepts of big data machine learning
Principles and techniques of big data machine learning
Algorithms of machine learning and deep learning

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches the theoretical basis of big data machine learning for college students

Strengthens big data machine learning methods and solutions for college students

Develops machine learning and deep learning algorithms for college students

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Big Data Machine Learning | 大数据机器学习 with these activities:

Review statistical learning theory

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Brush up on statistical learning theory to refresh your prerequisite knowledge and prepare for this course

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Review the basic concepts of statistical learning
Revisit different statistical learning methods
Solve practice problems to reinforce your understanding

阅读《机器学习实战》

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阅读经典教材《机器学习实战》可以补充你的课堂学习，并加深你对机器学习概念和算法的理解。

View Machine Learning with Python dialysis combat... on Amazon

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购买或借阅《机器学习实战》
仔细阅读每一章并做笔记
完成书中的练习和项目

Join a study group for this course

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Enhance your learning experience and clarify concepts by actively engaging with peers

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Find other students in this course and form a study group
Meet regularly to discuss course materials
Work together on practice problems and assignments

Three other activities

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Solve practice problems on machine learning algorithms

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Strengthen your understanding of machine learning algorithms through solving practice problems

Browse courses on Machine Learning Algorithms

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Identify the different types of machine learning algorithms
Practice implementing these algorithms in your preferred programming language
Analyze the performance of your algorithms on different datasets

Follow a tutorial series on deep learning

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Expand your knowledge of deep learning by following a structured tutorial series

Browse courses on Deep Learning

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Identify a reputable tutorial series on deep learning that covers the topics you want to learn
Follow the tutorials step-by-step, completing all exercises and activities
Apply what you have learned to a small project or experiment

Write a summary of a research paper on deep learning

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Enhance your understanding of deep learning and develop your scientific writing skills

Browse courses on Deep Learning

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Select a recent research paper on deep learning
Read and understand the paper thoroughly
Summarize the main findings and contributions of the paper in your own words
Discuss the implications of the paper for the field of deep learning

Career center

Learners who complete Big Data Machine Learning | 大数据机器学习 will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist gathers, interprets, and analyzes data to extract insights that drive business decisions and improve outcomes. The course "Big Data Machine Learning | 大数据机器学习" provides a solid foundation in data analysis and machine learning techniques, which are essential for success in this role. By taking this course, you'll gain the skills and knowledge to effectively manage and analyze large datasets, enabling you to make data-driven decisions and contribute to the success of organizations.

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Machine Learning Engineer

Machine Learning Engineers design, develop, and deploy machine learning solutions to solve complex problems. The course "Big Data Machine Learning | 大数据机器学习" provides a deep understanding of machine learning algorithms and techniques, as well as experience in working with big data. This course will equip you with the skills to build and implement machine learning models that can handle large and complex datasets, making you a valuable asset to organizations seeking to leverage machine learning for their business needs.

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Data Analyst

Data Analysts collect, clean, and analyze data to provide insights that help businesses make better decisions. The course "Big Data Machine Learning | 大数据机器学习" provides a comprehensive understanding of data analysis techniques and tools. By taking this course, you'll develop the skills to effectively gather, process, and analyze large amounts of data, enabling you to identify trends, patterns, and insights that can drive business growth and competitive advantage.

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Software Engineer

Software Engineers design, develop, and maintain software applications. The course "Big Data Machine Learning | 大数据机器学习" provides a solid foundation in machine learning and data analysis, which are increasingly important in software development. By taking this course, you'll gain the skills to incorporate machine learning techniques into your software applications, enabling you to develop more intelligent and efficient software solutions.

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Business Intelligence Analyst

Business Intelligence Analysts use data to understand business performance and identify opportunities for improvement. The course "Big Data Machine Learning | 大数据机器学习" provides a deep understanding of data analysis techniques and machine learning algorithms. By taking this course, you'll gain the skills to extract insights from large and complex datasets, enabling you to make data-driven recommendations and drive business growth.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data and make investment decisions. The course "Big Data Machine Learning | 大数据机器学习" provides a strong foundation in machine learning and data analysis, which are essential for success in this role. By taking this course, you'll gain the skills to develop and implement quantitative models that can help you make informed investment decisions and achieve superior returns.

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Data Architect

Data Architects design and manage the architecture of data systems, ensuring that data is stored and processed efficiently. The course "Big Data Machine Learning | 大数据机器学习" provides a deep understanding of data management techniques and big data technologies. By taking this course, you'll gain the skills to design and implement data architectures that can handle large and complex datasets, enabling you to support the growing data needs of organizations.

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Database Administrator

Database Administrators manage and maintain databases, ensuring that data is stored and processed efficiently. The course "Big Data Machine Learning | 大数据机器学习" provides a solid foundation in data management techniques and big data technologies. By taking this course, you'll gain the skills to manage and maintain large and complex databases, enabling you to ensure the integrity and availability of data for critical business operations.

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Data Engineer

Data Engineers build and maintain the infrastructure that supports data analysis. The course "Big Data Machine Learning | 大数据机器学习" provides a deep understanding of big data technologies and data management techniques. By taking this course, you'll gain the skills to design and implement data pipelines and infrastructure that can handle large and complex datasets, enabling you to support the growing data needs of organizations.

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Statistician

Statisticians collect, analyze, and interpret data to provide insights and solve problems. The course "Big Data Machine Learning | 大数据机器学习" provides a solid foundation in statistical methods and machine learning algorithms. By taking this course, you'll gain the skills to design and conduct statistical studies, analyze data, and draw meaningful conclusions, enabling you to contribute to evidence-based decision-making and problem-solving.

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Market Researcher

Market Researchers conduct research to understand consumer behavior and market trends. The course "Big Data Machine Learning | 大数据机器学习" provides a deep understanding of data analysis techniques and machine learning algorithms. By taking this course, you'll gain the skills to collect and analyze market data, identify trends and patterns, and develop insights that can help businesses make informed decisions and gain a competitive advantage.

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Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. The course "Big Data Machine Learning | 大数据机器学习" provides a solid foundation in statistical methods and machine learning algorithms. By taking this course, you'll gain the skills to develop and implement actuarial models that can help you assess risk, set premiums, and make informed decisions, enabling you to contribute to the financial stability of organizations.

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Risk Analyst

Risk Analysts identify and assess risks that organizations face. The course "Big Data Machine Learning | 大数据机器学习" provides a deep understanding of statistical methods and machine learning algorithms. By taking this course, you'll gain the skills to collect and analyze risk data, identify and quantify risks, and develop mitigation strategies, enabling you to help organizations make informed decisions and manage risk effectively.

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Credit Analyst

Credit Analysts assess the creditworthiness of borrowers and make lending decisions. The course "Big Data Machine Learning | 大数据机器学习" provides a solid foundation in statistical methods and machine learning algorithms. By taking this course, you'll gain the skills to develop and implement credit scoring models that can help you assess the risk of default, set credit limits, and make informed lending decisions, enabling you to contribute to the financial stability of organizations.

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Fraud Analyst

Fraud Analysts investigate and prevent fraud. The course "Big Data Machine Learning | 大数据机器学习" provides a deep understanding of data analysis techniques and machine learning algorithms. By taking this course, you'll gain the skills to detect and investigate fraud, develop fraud detection models, and implement fraud prevention measures, enabling you to protect organizations from financial losses and reputational damage.

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