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Neural Networks for Machine Learning

Geoffrey Hinton

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machine learning artificial neural networks ai deep learning human motion modeling language image segmentation

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Teaches how AI is used in fields such as speech recognition, object detection, image segmentation, and language modeling

Suitable for learners with intermediate-level calculus and programming skills

Instructors are Geoffrey Hinton, a leading expert in artificial neural networks

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Reviews summary

Beginner-friendly neural networks

"Neural Networks for Machine Learning" provides a beginner-friendly introduction to the fundamentals of neural networks and their applications in machine learning. Students describe the course as being well-structured and appreciate Prof. Hinton's expertise and passion for the subject. Although some reviewers note the course's difficulty and recommend it for those with a strong mathematical background, the overall feedback suggests that students find the course valuable and rewarding.

Well-structured and organized

"This course is well-structured"

Emphasizes practical applications of neural networks

"It is not easy, but is is definitely worth the effort."

Covers real-world applications of neural networks

"Great course. If you are serious about machine learning this is the course."

Led by renowned researcher Prof. Hinton

"One of the leading lights of Neural Networks"

Course requires a strong mathematical foundation

"An astoundingly-difficult course to complete"

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Career center

Learners who complete Neural Networks for Machine Learning will develop knowledge and skills that may be useful to these careers:

Machine Learning Researcher

A Machine Learning Researcher researches the development and application of methods and algorithms for machine learning. This course may be useful for someone working or looking to work as a Machine Learning Researcher who is interested in learning more about neural network applications in machine learning and how they can be applied in different areas.

See salaries and explore the career path for Machine Learning Researcher

Robotics Engineer

A Robotics Engineer designs, builds, and maintains robots. This course may be useful for someone working or looking to work as a Robotics Engineer who is interested in learning more about neural network applications in machine learning and how they can be used in the field of robotics, such as for human motion or gesture recognition.

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Natural Language Processing Engineer

A Natural Language Processing Engineer designs and builds systems that can process and interpret human language. This course may be useful for someone working or looking to work as a Natural Language Processing Engineer who is interested in learning more about neural network applications in machine learning and how they relate to modelling language.

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Computer Vision Engineer

A Computer Vision Engineer designs and builds systems that can interpret images and video. This course may be useful for someone working or looking to work as a Computer Vision Engineer who is interested in learning more about neural network applications in machine learning as they relate to image segmentation and object recognition.

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Neural Network Engineer

A Neural Network Engineer designs, builds, deploys, tests, and maintains neural network systems. This course may be useful for someone working or looking to work as a Neural Network Engineer who is interested in learning more about neural network applications in machine learning and how they can be leveraged to solve problems in speech and object recognition, image segmentation, modeling language, and human motion.

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Artificial Intelligence Engineer

An Artificial Intelligence Engineer uses machine learning, neural networks, and deep learning to develop new technologies that are capable of performing tasks that typically require human intelligence. This course may be useful for someone working or looking to work as an Artificial Intelligence Engineer who is interested in learning more about neural network applications in machine learning and how they can be leveraged.

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Deep Learning Engineer

A Deep Learning Engineer uses machine learning, neural networks, and deep learning to develop new technologies that are capable of performing tasks that typically require human intelligence. This course may be useful for someone working or looking to work as a Deep Learning Engineer who is interested in learning more about neural network applications in machine learning and how they can be leveraged.

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Biostatistician

A Biostatistician applies statistical methods to medical data to answer research questions. This course may be useful for someone working or looking to work as a Biostatistician who wants to learn more about neural networks and how they can be applied to medical research.

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Data Engineer

A Data Engineer builds and maintains data infrastructure for analytics and data science teams. This course may be useful for someone working or looking to work as a Data Engineer who is interested in expanding their knowledge of neural networks and their applications in machine learning.

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Quantitative Analyst

A Quantitative Analyst uses mathematical and statistical models to analyze and predict financial trends. This course may be useful for someone working or looking to work as a Quantitative Analyst who is interested in applying machine learning methods to financial data.

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Data Analyst

A Data Analyst mines data to uncover insights and trends that can be used for new product development, customer segmentation, and process optimization. This course may be useful for someone working or looking to work as a Data Analyst who is interested in expanding their knowledge of neural networks so they can apply these principals to their own work.

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Computer Scientist

A Computer Scientist is responsible for the research and design of computer systems and software. They test and analyze the latest trends and technologies to determine next steps for developing methodologies, algorithms, and programming languages. This course may be useful for a Computer Scientist who is interested in learning neural network applications in machine learning and expanding their knowledge of how they can be utilized.

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Software Engineer

A Software Engineer creates, deploys, and maintains software systems. They work with everything from big data to cloud computing. This course may be useful for someone working or looking to work as a Software Engineer and wants to learn more about neural network applications as they apply to speech and object recognition, image segmentation, modeling language, and human motion.

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Data Scientist

A Data Scientist works to collect, review, and interpret data using statistical techniques. They engage in forecasting and risk assessment as well as solve business problems or find new opportunities for the business. This course may be useful for someone working or looking to work as a Data Scientist who is interested in expanding their knowledge of neural networks, especially as applied to speech and object recognition, image segmentation, modeling language, and human motion.

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Machine Learning Engineer

A Machine Learning Engineer is a computer scientist that builds, designs, and maintains machine learning systems. They take steps to refine and debug the code based on the data gathered and any goals that need to be met. This course may be useful for someone working or looking to work as a Machine Learning Engineer who is interested in expanding their skillset to include neural network applications in machine learning. They will learn how to utilize this tool and what techniques they can use to make it work to their advantage.

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