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Machine Learning courses

1003 Courses

California Institute of Technology Udemy

The Complete Artificial Intelligence and ChatGPT Course

The Complete Artificial Intelligence and ChatGPT Course The Complete Artificial Intelligence and ChatGPT Course Includes ChatGPT Alternatives Google Bard & Bing Chat, Machine Learning, Images with DALL-E & Midjourney, Voice & More. University: Provider: Udemy Categories: Artificial Intelligence Cour.
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provider Udemy
pricing Paid Course
duration 12 hours
sessions On-Demand
California Institute of Technology AWS Skill Builder

Unleashing Innovation: The Generative AI Revolution

Unleashing Innovation: The Generative AI Revolution We find ourselves in a society where the line between what is created by humans, and what is created by machines, is increasingly blurred. Generative AI has been a turning point in how we create, design, and interact with technology. But how does it work, what are the benefits beyond novelty and.
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provider AWS Skill Builder
pricing Free Certificate
duration 1 hour 50 minutes
sessions On-Demand
California Institute of Technology Kadenze

Machine Learning for Music Information Retrieval

An introduction to data mining through the lens of music information retrieval. Topics explored include classification (genre, mood, instrument), multi-label classification (tagging), and regression (emotion/mood). University: Provider: Kadenze Categories: Machine Learning Courses, Data Mining Courses, Regression Analysis Courses
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provider Kadenze
pricing $350.00
duration 50 hours
sessions On-Demand
California Institute of Technology Stanford University

Stanford Seminar - Audio Research: Transformers for Applications in Audio, Speech and Music

Stanford Seminar - Audio Research: Transformers for Applications in Audio, Speech and Music Course Title: Stanford Seminar - Audio Research: Transformers for Applications in Audio, Speech and Music Description: This course aims to teach learners about the applications of Transformers in audio, speech, and music. The learning outcomes include und.
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California Institute of Technology Stanford University

Stanford Seminar - Can the Brain Do Back-Propagation?

Stanford Seminar - Can the Brain Do Back-Propagation? This course explores the concept of whether the brain can perform back-propagation. The learning outcomes include understanding online stochastic gradient descent, reasons why the brain may not be able to do backprop, and new methods for unsupervised learning. Students will learn about the.
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California Institute of Technology Stanford University

Bayesian Networks 1 - Inference - Stanford CS221: AI

Bayesian Networks 1 - Inference - Stanford CS221: AI The course teaches students how to specify joint distributions compactly using Bayesian networks and factor graphs. It covers probabilistic inference, explaining away, consistency of sub-Bayesian networks, and applications such as medical diagnosis, language modeling, object tracking, multiple.
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California Institute of Technology Stanford University

Stanford Seminar - Accessibility and the AI Autumn - Jeff Bigham

Stanford Seminar - Accessibility and the AI Autumn - Jeff Bigham This course aims to educate learners on the importance of accessibility in the context of artificial intelligence. The learning outcomes include understanding human-computer interaction, challenging ability assumptions, designing for users with disabil.
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provider YouTube
pricing Free Online Course
duration 1 hour
sessions On-Demand
California Institute of Technology Stanford University

Stanford Seminar - Distributed Perception and Learning Between Robots and the Cloud

University: Stanford University Provider: YouTube Categories: Machine Learning Courses, Reinforcement Learning Courses, Federated Learning Courses This course aims to teach learners about distributed perception and learning between robots and the cloud. The learning outcomes include understanding the key challenges of cloud robotics, distribu.
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provider YouTube
pricing Free Online Course
duration 47 minutes
sessions On-Demand
California Institute of Technology Skillshare

Artificial Intelligence for Beginners: Tools to Learn Machine Learning

Artificial Intelligence for Beginners: Tools to Learn Machine Learning What really is “artificial intelligence”? “Machine learning”? Let’s cut through the meaningless buzzwords, and talk the real talk. This class covers must-know topics for AI product managers, ML practitioners, and anyone in between that’s curious about these emerging fields. We.
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provider Skillshare
pricing Free Trial Available
duration 1 hour 5 minutes
sessions On-Demand
California Institute of Technology University of Queensland

Teaching Impacts of Technology: Data Collection, Use, and Privacy

Teaching Impacts of Technology: Data Collection, Use, and Privacy In this course, you'll delve into the influence of constant data collection and big data analysis on daily life. Discover the fine balance between using and safeguarding your data, and consider its potential future benefits. The journey includes paired teaching sections that exami.
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More and more products are now being developed using artificial intelligence. To avoid being left on the sidelines of progress, managers must understand how the robot’s “brains” work

Artificial intelligence (AI) and machine learning technologies have been used for many years, but now the intensity of their use has increased significantly. For example, machine learning is being actively implemented in telecommunications, retail, marketing and e-commerce. But many still do not fully understand what it is.

Machine learning involves the system processing a large number of examples, during which it identifies patterns and uses them to predict the characteristics of new data. In other words, this is the process of giving AI ml courses “consciousness”, the ability to remember and analyze.

Machine learning use cases

The use of machine learning has touched many areas in our lives. Let's look at the most striking examples of the use of computer intelligence:

Facial recognition in the subway will help identify violators or criminals in a huge mass of people. Ordinary observers cannot cope with this task. But a fast-learning machine will do this job without any problems.

What do you need for machine learning (ML)?

For those interested in training, there are several requirements to be met in order to be successful in this field. So, there are the main points you need to know about the machine learning course. These requirements include:

  1. Basic knowledge of programming languages such as Python, R, Java, JavaScript, etc.

  2. Average knowledge of statistics and probability.

  3. Basic knowledge of linear algebra in the ml course. In a linear regression model, a line is drawn through all the data points, and that line is used to calculate new values.

  4. Understanding Calculus.

  5. Knowledge of how to clean and structure raw data into the desired format to reduce the time required for decision making.

Machine learning courses from AI Eeducation are the best choice!