Machine Learning courses

1003 Courses

Explainable Machine Learning (XAI)

Explainable Machine Learning (XAI) Explainable Machine Learning (XAI) As Artificial Intelligence (AI) becomes integrated into high-risk domains like healthcare, finance, and criminal justice, it is critical that those responsible for building these systems think outside the black box and develop systems that are not only accurate, but also trans.

edX

Inteligencia Artificial en la Logística

Inteligencia Artificial en la Logística Este curso integral está diseñado para profesionales y entusiastas de la logística que desean profundizar en el uso y aplicación de la inteligencia artificial (IA) en sus operaciones diarias. A lo largo de cuatro módulos detallados, los participantes explorarán cómo la IA está revoluciona.

Coursera

Selecting the Right LLM with Hugging Face

There are literally thousands of Large Language Models or LLMs available out there that can be used for a plethora of purposes. Hugging Face is the de-facto hub for language models, offering a huge collection where you can find and use almost any model you need. Choosing the right model can be an arduous task given models come in various shape.

Udacity

Introduction to Self-Driving Cars

Introduction to Self-Driving Cars | Udacity Discover how to build a self-driving car with this comprehensive course from Udacity. Covering essential topics such as probability, C++, machine learning, and linear algebra, this course equips you with the knowledge needed to excel in the field of autonomous vehicles. Categories.

Udacity

AI for Trading

AI for Trading | Udacity Complete real-world projects designed by industry experts, covering topics from asset management to trading signal generation. Master AI algorithms for trading, and build your career-ready portfolio. University: Provider: Udacity Categories: Artificial Intelligence Courses Python Courses Machine Learning Courses.

Udacity

AI For Business Leaders

AI For Business Leaders | Udacity AI For Business Leaders University: Udacity Categories: Artificial Intelligence Courses, Machine Learning Courses, Business Courses Formulate and evaluate proposals grounded in first principles when assessing opportuniti.

Udacity

Self Driving Car Engineer

Self Driving Car Engineer Work on the future of autonomous vehicles and help make the self-driving car revolution a reality! University: Provider: Udacity Categories: Machine Learning Courses, Computer Vision Courses, Deep Learning Courses, Autonomous Vehicles Courses, Kalman Filter Courses, Image Processing Courses, Localization Courses, PID C.

Udacity

Applying Data Science to Product Management

Applying Data Science to Product Management All products developed for today's market are data products—running on data-derived insights to provide the right experience, to the right user, at the right time. Companies like Amazon, Netflix, Google, and more are able to provide personalized and engaging experiences to users because they utilize.

Udacity

AWS Machine Learning Engineer Nanodegree

AWS Machine Learning Engineer Nanodegree The AWS Machine Learning Engineer (MLE) Nanodegree program aims to equip software developers and data scientists with essential data science and machine learning skills. Learn to build and deploy machine learning models in production using Amazon SageMaker. This comprehensive course focuses on the latest bes.

Coursera

Work with Gemini Models in BigQuery - 日本語版

Gemini モデルを使用した BigQuery 作業 - 日本語版このコースでは、BigQueryで生成型AI作業にAI/MLモデルを使用する方法を紹介します。顧客関係管理に関連する実際の使用事例を通じて、Geminiモデルを使用してビジネス問題を解決するワークフローを解説します。理解を深めるために、SQLクエリとPythonノートブックを使用したコードソリューションを詳細に案内します。

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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!