Machine Learning courses

1334 Courses

Coursera

Using Gemini in Education

Using Gemini in Education Join our self-paced lab on the Google Cloud console to explore the potential of Gemini models in transforming educational experiences. This hands-on course, provided by Coursera, is designed for those eager to integrate cutting-edge AI and machine learning technologies into educational environments. Offered by: Coursera.

Coursera

Getting started with the Vertex AI Gemini 1.5 Pro Model

Getting Started with the Vertex AI Gemini 1.5 Pro Model Getting Started with the Vertex AI Gemini 1.5 Pro Model Immerse yourself in a self-paced lab within the Google Cloud console, designed to offer an introductory and practical experience with Generative AI on Google Cloud. This engaging lab is provided by Coursera. Categories: A.

Coursera

Custom Document Extraction with Document AI Workbench

Custom Document Extraction with Document AI Workbench Experience hands-on learning with this self-paced lab in the Google Cloud console. During this lab, you will master the creation and training of a Custom Document Extractor specifically designed for processing W-2 (US tax form) documents. University: Coursera Categories: Machine Learning Cour.

Coursera

PyTorch Ultimate 2024 - From Basics to Cutting-Edge

PyTorch Ultimate 2024 - From Basics to Cutting-Edge Embark on a transformative learning experience with our PyTorch Ultimate 2024 course. Begin with a solid foundation, understanding the key topics and objectives, and seamlessly transition through machine learning essentials and deep learning principles. From setting up your environment to master.

Coursera

Uptraining with Document AI Workbench

Title: Uptraining with Document AI Workbench Description: Embark on a self-paced lab within the Google Cloud console where you'll build an Invoice Parser processor, configure it for uptraining, label example documents, and enhance the processor’s capabilities. University: Provider: Coursera Categories: Machine Learning Courses,.

Coursera

Optical Character Recognition (OCR) with Document AI (Python)

Coursera

Form Parsing with Document AI (Python)

Form Parsing with Document AI (Python) Embark on this self-paced lab in the Google Cloud console where you will develop skills in using the Document AI Form Parser to parse handwritten forms using Python. Offered by Coursera, this lab is an essential resource for those interested in Python, machine learning, Google Cloud Platform, document AI, d.

Coursera

Call Gemini using the OpenAI Library

Call Gemini using the OpenAI Library University: Provider: Coursera Categories: Python Courses, Machine Learning Courses, Google Cloud Platform (GCP) Courses, Gemini Courses, OpenAI Courses This self-paced lab, hosted in the Google Cloud console, guides you through the process of calling Gemini using the OpenAI library. Enhance your skills an.

Coursera

Build and Deploy an Agent with Reasoning Engine in Vertex AI

Build and Deploy an Agent with Reasoning Engine in Vertex AI Engage in this self-paced lab through the Google Cloud console and gain hands-on experience in building and deploying an agent. Learn to utilize the Vertex AI SDK for Python effectively, including working with models, tools, and reasoning. Categories: Artificial Intelligence Cour.

Coursera

Build a DIY Multimodal Question Answering System with Vertex AI

Build a DIY Multimodal Question Answering System with Vertex AI Join this self-paced lab in the Google Cloud console to master building a question answering system capable of understanding both text and images with Vertex AI. Perfect for those interested in Artificial Intelligence, Machine Learning, Computer Vision, and Google Cloud Platform..

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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!