Machine Learning courses

1003 Courses

Inteligencia Artificial & ChatGPT: De Cero a Avanzado 2024

Inteligencia Artificial & ChatGPT: De Cero a Avanzado 2024 El curso completo de Inteligencia Artificial: Chat GPT, IA Generativa, LLMs, IA Prompt Engineering, Midjourney y más! Ofrecido por: Udemy Categorías: Cursos de Inteligencia Artificial, Cursos de Aprendizaje Automático, Cursos de Aprendizaje Profundo, Cursos de ChatGPT
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ChatGPT Masterclass - The Ultimate Guide

ChatGPT Masterclass - The Ultimate Guide Unlock the full potential of ChatGPT and generative AI with our comprehensive masterclass. Dive deep into prompt engineering, explore Midjourney, and enhance your skills in data science, programming, and APIs. This course, available on Udemy, is a must for anyone looking to excel in the field of artificia.
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Introduction à l'apprentissage profond

Introduction à l'apprentissage profond Développé par IVADO et le MILA, ce cours d'une durée totale de 5 heures présente les concepts fondamentaux de l'apprentissage profond à travers 5 modules de formation proposés en français. Le contenu sera présenté à l’aide de vidéos pédagogiques présentés par des spécialistes du domaine : Alain Tapp, Yoshua B.
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AI Infrastructure and Operations Fundamentals

AI Infrastructure and Operations Fundamentals Artificial Intelligence, or AI, is transforming society in many ways. From speech recognition to self-driving cars, to the immense possibilities offered by generative AI. AI technology provides enterprises with the compute power, tools, and algorithms their teams need to do t.
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Developing Generative Artificial Intelligence Solutions

Developing Generative Artificial Intelligence Solutions In this course, you will explore the generative artificial intelligence (generative AI) application lifecycle, which includes the following: Defining a business use case Selecting a foundation model (FM) Improving the performance of an FM Evaluating the performa.
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Responsible Artificial Intelligence Practices

Responsible Artificial Intelligence Practices In this course, you will learn about responsible AI practices. First, you will be introduced to what responsible AI is. You will learn how to define responsible AI, understand the challenges that responsible AI attempts to overcome, and explore the core dimensions of responsible AI. Then, you will dive.
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Exploring Artificial Intelligence Use Cases and Applications

Exploring Artificial Intelligence Use Cases and Applications In this course, you will explore real-world artificial intelligence (AI), machine learning (ML), and generative artificial intelligence (generative AI) use cases across a range of industries. These areas include healthcare, finance, marketing, entertainment, and more. You will also learn.
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Fundamentals of Machine Learning and Artificial Intelligence

Fundamentals of Machine Learning and Artificial Intelligence In this course, you will learn about the foundations of machine learning (ML) and artificial intelligence (AI). You will explore the connections between AI, ML, deep learning, and the emerging field of generative artificial intelligence (generative AI). You will gain a solid understanding.
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AWS ML Engineer Associate 2.1 Choose a Modeling Approach

AWS ML Engineer Associate 2.1 Choose a Modeling Approach Explore the AWS ML stack layers and learn how to solve common business challenges with AWS services. This course explores how to use Amazon SageMaker for machine learning tasks and how to review strategies for selecting appropriate models. Additionally, this course highlig.
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Optimizing Foundation Models (Simplified Chinese)

优化基础模型 (简体中文) 在本课程中,您将探索两种可提高基础模型 (FM) 性能的技术:检索增强生成 (RAG) 和微调。您将了解有助于使用向量数据库存储嵌入的 Amazon Web Services (AWS) 服务、代理在多步骤任务中的作用、定义微调 FM 的方法以及如何准备用于微调的数据等等。 课程级别:基础级 时长:1 小时 本课程包含互动元素、文字说明、配文图表和知识考核。 在本课.
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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!