Machine Learning courses

1003 Courses

AWS Cloud Quest: Generative AI (Japanese) 日本語版

AWS Cloud Quest: Generative AI (Japanese) 日本語版 Join the AWS Cloud Quest: Generative AI program in Japanese and enhance your skills in a variety of AWS services. Amazon S3 AWS Lambda Amazon EC2 Amazon API Gateway Amazon CloudFront Amazon SageMaker Amazon DynamoDB AWS Cloud 9 Amazon OpenSearch Service Amazon Comprehend.
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Responsible AI for Developers: Fairness & Bias

Course Title: Responsible AI for Developers: Fairness & Bias Description: This course introduces fundamental concepts of responsible AI and core AI principles. Attendees will learn practical techniques for identifying and mitigating fairness and bias issues in AI/ML. The curriculum includes hands-on methods and tools to implement Responsible AI bes.
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Gemini: Prompt Engineering for Data Professionals

Gemini: Prompt Engineering for Data Professionals Gemini offers powerful support for data professionals seeking to accelerate their analysis. This course will teach you how to leverage Gemini's capabilities to streamline your projects effectively. The ability to quickly extract actionable insights from complex datasets is essential for business.
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Developing Machine Learning Solutions (Portuguese)

Developing Machine Learning Solutions (Portuguese) Neste curso de machine learning, você aprenderá sobre o ciclo de vida do machine learning e como usar os serviços da AWS em todas as etapas. Além disso, você descobrirá as diversas fontes de modelos de machine learning e aprenderá técnicas para avaliar seu desempenho. Você ta.
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Azure Machine Learning Development: 2 Learning ML Studio

Azure Machine Learning Development: Learning ML Studio University: - Provider: LinkedIn Learning Categories: Machine Learning Courses, Microsoft Azure Courses, Data Analysis Courses, Data Cleaning Courses, Model Evaluation Courses, Model Training Courses
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Foundations of Machine Learning

Foundations of Machine Learning | University | Provider Discover the foundational concepts of machine learning in this comprehensive course. You'll cover essential topics, including data representation, model building, neural networks, and the intricate learning processes that power AI. Hands-on experience with Flux.jl, a sophisticated.

Machine Learning Essentials for Business and Technical Decision Makers

Machine Learning Essentials for Business and Technical Decision Makers | Coursera In this course, you will learn about best practices and recommendations for machine learning (ML). The course explores how to roadmap for integrating ML into your business processes, explores requirements to determine if ML is the appropriate solution to a business.
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Developing Machine Learning Solutions

In this machine learning course, you will learn about the machine learning lifecycle and how to use AWS services at every stage. Additionally, you will discover the diverse sources for machine learning models and learn techniques to evaluate their performance. You will also understand the importance of machine learning operations (MLOps) in str.
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Fine-tuning Language Models for Business Tasks

Fine-tuning Language Models for Business Tasks This course demystifies the concept of "LLM fine-tuning" and its critical applications in the business world. In the context of rapidly evolving AI technologies, understanding how to fine-tune Large Language Models (LLMs) is essential for businesses to stay competitive. The course covers foundationa.
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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!