Machine Learning courses

1336 Courses

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.

Apache Spark Essential Training

Apache Spark Essential Training Apache Spark Essential Training Get up to speed with Spark, and discover how to leverage this powerful platform to efficiently and effectively work with big data. Categories: Machine Learning Courses, Big Data Courses, Data Analysis Courses, Apache Spark Courses

Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions

Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions Unlock the potential of AI with our specialized course on Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions. Gain expertise in creating AI models that are not only powerfu.

Advance Your Skills as an Apache Spark Specialist

Advance Your Skills as an Apache Spark Specialist Apache Spark is among the fastest-growing tools in data science, due to its streaming, speed, and scalability capabilities. In particular, the Spark MLlib machine learning library is rapidly becoming a must-have for those working in AI. Stay up to date with the latest Apache Spark skills. Cat.

Azure Machine Learning Development: 1 Basic Concepts

Are you interested in developing solutions with Azure Machine Learning? This course offers a clear and concise introduction to machine learning and data science. Learn the fundamental concepts and get started on your journey to mastering Azure Machine Learning today. Course Provider: [University Name] Categories: Artificial Intelligence Cour.

DJ Patil: Ask Me Anything

DJ Patil: Ask Me Anything Join former U.S. chief data scientist DJ Patil as he tackles questions posed by LinkedIn members. Topics range from data security to the future of data science. Categories: Artificial Intelligence Courses Machine Learning Courses Neural Networks Courses Data Science Courses Internet of Things Courses Cyber.

Machine Learning and AI Foundations: Causal Inference and Modeling

Machine Learning and AI Foundations: Causal Inference and Modeling Enroll in our comprehensive course, "Machine Learning and AI Foundations: Causal Inference and Modeling," and delve into the essential modeling techniques and experimental designs that are crucial for establishing causal inference. Enhance your understanding and.

Digital Transformation Tips

Digital Transformation Tips Learn how to best support the digital transformation efforts of your business. Get actionable tips for leveraging technology and planning for success. Categories: Artificial Intelligence Courses Machine Learning Courses Big Data Courses Digital Transformation Courses Cloud Computing Courses Internet of T.

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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!