Machine Learning courses

1656 Courses

DataCamp

Working with Hugging Face

Navigate and use the extensive repository of models and datasets available on the Hugging Face Hub. In today's rapidly evolving landscape of machine learning (ML) and artificial intelligence (AI), Hugging Face stands out as a vital platform, allowing anyone to leverage the latest advancements in their projects. To begin, you'll navigate the Hug.

AWS Skill Builder

Machine Learning on AWS

Join the Machine Learning on AWS program where interactive challenges foster skill development in a fun and engaging environment. Perfect for those aiming to acquire practical skills applicable to real-world scenarios, this course utilizes AWS services to elevate your learning experience. Demonstrate your proficiency and earn recognition by co.

DataCamp

Understanding Data Topics

Learn to understand data and why it’s so important in today’s world. You’ll also gain the fundamental data skills you need to speak the language of data. There are no prior knowledge or coding skills required for this track. Instead, you’ll learn how to understand and interpret data through hands-on exercises, whether it’s through a bar plot on the.

edX

Applications of AI in Healthcare

Artificial Intelligence (AI) plays a pivotal role in advancing healthcare by addressing major diseases and mortality causes. Through real-time data sharing and insights derived from AI, significant strides are made in diagnosing and treating various health conditions. AI's specific applications in healthcare enhance patient care through machine lea.

DataCamp

AI Fundamentals

Embark on an exciting journey through the realms of Artificial Intelligence with DataCamp's AI Fundamentals course. This comprehensive program enables you to conquer AI frontiers and harness the power of generative AI and sophisticated large language models. Designed to lay a strong foundation, this course will propel you into the emerging A.

DataCamp

AI Business Fundamentals

Equip yourself with vital AI knowledge and tools to make an immediate impact in the fast-evolving world of Artificial Intelligence (AI). Our courses are tailored for professionals eager to harness the power of AI and place themselves at the forefront of the AI revolution. With a focus on AI strategy, you'll learn to utilize generative AI an.

DataCamp

Data Skills for Business

Join the 'Data Skills for Business' course by DataCamp and enrich your knowledge in core data concepts. Equip yourself with the skills to answer real-world questions using data and enhance your ability as a data-driven decision-maker within your organization. Data is an invaluable resource in the modern world, making it essential to comprehend a.

DataCamp

EU AI Act Fundamentals

Start your journey in Artificial Intelligence with DataCamp's EU AI Act Fundamentals course, specifically tailored for business professionals. This course provides a robust foundation in AI principles while offering in-depth insights into the newly ratified EU AI Act. Participants will explore how to leverage AI technologies to devise impact.

DataCamp

Llama Fundamentals

Join the Llama Fundamentals track offered by DataCamp and gain the essential skills to implement Llama 3 in a variety of tasks. From running inference on pre-trained models to fine-tuning for custom use cases, this track is designed to prepare you for practical applications. Engage with the open-source Llama model in diverse applications a.

DataCamp

ChatGPT Fundamentals

Embark on a journey to harness the power of AI with the ChatGPT Fundamentals course offered by DataCamp. This foundational course is designed to introduce you to the essentials of ChatGPT, enabling you to craft effective prompts and transform workflows. Through this course, you will discover how businesses worldwide utilize ChatGPT to drive.

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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!