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Machine Learning courses

1736 Courses

California Institute of Technology AWS Skill Builder

Fundamentals of Machine Learning and Artificial Intelligence (日本語)

Fundamentals of Machine Learning and Artificial Intelligence (日本語) - AWS Skill Builder このコースでは、機械学習 (ML) と人工知能 (AI) の基礎について学びます。AI、ML、深層学習、そして生成人工知能 (生成 AI) という新たな分野の関係を探ります。基本的な AI 用語をしっかりと理解し、これらの概念をより深く掘り下げるための基礎を築きます。さらに、AI と ML.
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California Institute of Technology AWS Skill Builder

Exploring Artificial Intelligence Use Cases and Applications (繁體中文)

在本課程中，您將探索各種行業中人工智慧 (AI)、機器學習 (ML) 和生成人工智慧 (生成式 AI) 的實際使用案例。這些領域包括醫療保健、金融、行銷、娛樂等。您還將了解 AI、ML 和生成式 AI 功能和限制、模型選取技術，以及關鍵業務指標。 課程等級：基礎 課程時長：1 小時 注意：本課程具有本地化的註釋/字幕。旁白保留英語。要顯示字幕，請按一下播放器右下角的.
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California Institute of Technology AWS Skill Builder

Responsible Artificial Intelligence Practices (繁體中文)

Responsible Artificial Intelligence Practices (繁體中文) 在本課程中，您將學習 AI 實踐。首先，將為您介紹什麼是負責任的 AI。您將學習如何定義負責任的 AI、瞭解負責任的 AI 嘗試克服之挑戰，以及探索負責任 AI 的核心維度。 然後，您將深入探索一些主題，瞭解開發負責任的 AI 系統。將為您介紹由 AWS 提供，以協助您使用負責任的 AI 之服務和工具。您也將瞭解在為 AI.
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California Institute of Technology AWS Skill Builder

Developing Generative Artificial Intelligence Solutions (繁體中文)

在本課程中，您將會探索生成式人工智慧 (生成式 AI) 應用程式生命週期，其中包括以下內容： 定義商業使用案例 選取基礎模型 (FM) 改善 FM 的效能 評估 FM 的效能 部署及其對業務目標的影響 本課程是生成式 AI 課程的入門，其中深入探討使用提示詞工程、檢索增強生成 (RAG) 和微調來自訂 FM 的相關概念。 課程等級：基礎 課程時長：1 小時 注意：本課.
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California Institute of Technology AWS Skill Builder

Developing Generative Artificial Intelligence Solutions (日本語)

Developing Generative Artificial Intelligence Solutions (日本語) このコースでは、生成人工知能 (生成 AI) によるアプリケーションライフサイクルについて学びます。詳細は以下のとおりです。 ビジネスユースケースの定義 基盤モデル (FM) の選択 FM のパフォーマンスの改善 FM のパフォーマンスの評価 デプロイとビジネス目標への影響 このコースは生成 A.
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California Institute of Technology AWS Skill Builder

Exploring Artificial Intelligence Use Cases and Applications (日本語)

このコースでは、様々な産業領域における人工知能 (AI)、機械学習 (ML)、および生成AIの具体的なユースケースを探ります。これにはヘルスケア、金融、マーケティング、エンターテインメント業界が含まれ、AI技術の能力と限界、モデルの選択手法、主要なビジネスメトリクスを学びます。 コースレベル: 基礎 所要時間: 1時間 アクティビティこのコースは、インタラクテ.
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California Institute of Technology AWS Skill Builder

Responsible Artificial Intelligence Practices (日本語)

このコースでは、責任ある AI の実践について学びます。最初に、責任ある AI とは何かを説明します。責任ある AI の定義方法、直面している課題、その主な要素について学習します。 次に、責任ある AI システムを開発するためのトピックをいくつか取り上げます。責任ある AI をサポートするために AWS が提供しているサービスとツールを紹介します。また、AI システム用に.
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California Institute of Technology Udemy

A CEO's Generative AI Playbook

Discover the essential playbook for CEOs looking to integrate Generative AI into their business strategy. Offered by Udemy, this course offers a comprehensive guide to mastering the use of AI in a strategic context. You'll learn about Generative AI, Retrieval Augmented Generation (RAG), AI agents, and the integration of these advanced technolog.
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California Institute of Technology Udemy

Mastering AI on AWS: Training AWS Certified AI-Practitioner

Embark on a transformative journey with Udemy's "Mastering AI on AWS: Training AWS Certified AI-Practitioner." This course meticulously covers the development of AI and Machine Learning solutions using a range of AWS services, offering a deep dive from basic principles to achieving certification success. Leverage this opportunity to enhance you.
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California Institute of Technology Udemy

Harnessing AI and Machine Learning for Geospatial Analysis

Explore the fascinating world of artificial intelligence and machine learning as applied to geospatial analysis through our expertly crafted course. Enhance your skills in AI, deep learning, and machine learning techniques tailored for geospatial data. Offered by Udemy, this course dives deep into the intersection of these cutting-edge technol.
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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!