Machine Learning courses

1003 Courses

Coursera

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.

edX

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.

Udemy

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.

Udemy

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

Udemy

Learn Machine Learning Course with Python A to Z

Learn Machine Learning Course with Python A to Z Course Title: Learn Machine Learning Course with Python A to Z Description: Gain a solid understanding of machine learning concepts, algorithms, and applications in various fields. This comprehensive course offered by Udemy equips you with the skills needed to excel in the exciting field of machin.

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Vision artificielle et exploitation intelligente des ressources naturelles

Vision artificielle et exploitation intelligente des ressources naturelles Bienvenue au cours VIARENA, «Vision artificielle et exploitation intelligente des ressources naturelles». La vision artificielle est l'art et la science de rendre les ordinateurs capables d'interpréter intelligemment des images. Il existe une multitude d'applications de la.

Biodiversity Explorations with Machine Learning Study Group Sessions - Wolfram U

Biodiversity Explorations with Machine Learning Study Group Sessions - Wolfram U Summary Learn to apply machine learning techniques and Wolfram Language functions to biodiversity data. These Study Group sessions begin by introducing you to biodiversity data access functions available with the entity framework built into Wolfram Language and in t.

Coursera

Intro to Dall-E and GPT Vision

Intro to Dall-E and GPT Vision This course teaches you how to generate and manipulate high-quality images with OpenAI's Dall-E text-to-image model. You'll then discover how to get the most out of the model using the OpenAI API. Finally, you’ll integrate GPT-4 with Vision into your AI-powered apps to carry out comprehensive image analysis, inc.

Coursera

GenAI for Everyone

GenAI for Everyone This course offers a foundational journey into the world of Generative AI (GenAI), setting the stage for a comprehensive learning path that delves into the nuanced, role-specific applications of AI. Designed to equip learners with essential GenAI knowledge, this primer is the perfect starting point before progress.

Python pour le Deep Learning & le Machine Learning: A à Z

Python pour le Deep Learning & le Machine Learning: A à Z Plongez dans l'univers fascinant du Machine Learning avec notre cours complet Python pour le Deep Learning & le Machine Learning: A à Z. Ce programme détaillé vous guidera à travers les bases et les avancées nécessaires pour maîtriser l'intelligence artificielle, les outils TensorFlow, et.

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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:

Voice assistant Alisa. This system, without human help, will always find the answer to any question of interest, turn on music, answer the call and much more.

Selecting relevant advertising in browsers is not an easy process for a person, but it is quick for a computer. The system will analyze the viewing data and select what a particular user will like. The same system is used on various marketplaces - products that a person viewed or purchased are offered.

Chatbots in various dialogues. For example, many banks use bots to solve customer problems. It's convenient and fast.

Data security: Machine learning models can identify data security vulnerabilities before they become breaches. By analyzing past experiences, machine learning models can predict future high-risk actions so that risk can be mitigated proactively.

Finance: Banks, trading brokers and fintech firms use machine learning algorithms to automate trading and provide financial advisory services to investors. Bank of America uses chatbot Erica to automate customer support.

Healthcare: Machine learning is used to analyze massive medical data sets to speed up the discovery of treatments and cures, improve patient outcomes, and automate routine processes to prevent human errors. For example, IBM Watson uses data mining to provide doctors with data they can use to personalize patient care.

Fraud detection: AI is used in the finance and banking sector to autonomously analyze large numbers of transactions to identify fraudulent activities in real time. Technology services company Capgemini says fraud detection systems using machine learning and analytics reduce fraud investigation time by 70% and increase detection accuracy by 90% .

Retail: AI researchers and developers are using machine learning algorithms to develop AI recommendation engines that make relevant product suggestions based on shoppers' past choices, as well as historical, geographic and demographic data.

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:

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

Average knowledge of statistics and probability.

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.

Understanding Calculus.

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!