ML Fundamentals

Machine Learning Fundamentals Course

Artificial intelligence is a rapidly evolving field that is bringing about significant changes across the technology industry and virtually every aspect of our lives. Today's computers are capable of processing and analyzing vast amounts of data in less than a tenth of a second, and through the analysis and processing of data using artificial intelligence, we can enhance processes, draw conclusions, identify trends, and analyze various types of information across a wide range of fields and industries.

Machine Learning is an exciting branch of artificial intelligence that surrounds us. Machine learning harnesses the power of data in novel ways, such as Facebook suggesting articles in your feed. This remarkable technology assists computer systems in learning and improving from experience through the development of computer programs that can automatically access data and perform tasks through predictions and identifications.

When you feed more data into a machine, this action assists algorithms in training the computer, thus improving the provided results. For instance, when you ask Alexa to play your favorite music station on your Amazon Echo, it will choose a station you've been listening to frequently. You can further enhance and tailor your listening experience by instructing Alexa to skip songs, adjust the volume, and issue other various commands. Machine learning and the rapid advancements in artificial intelligence enable all of this.

Machine Learning involves the automatic learning of machines without being explicitly programmed or learned without direct human intervention. This machine learning process starts with inputting high-quality data and then training the machines by building various machine learning models using different data and algorithms. The choice of algorithms depends on the type of data we have and the type of automated task we are attempting.

In essence, it's a technique for data analysis that teaches computers to do what comes naturally to humans and animals: learn from experience. Machine Learning algorithms use computational methods to "learn" directly from data without relying on a fixed equation from beforehand, like a constant model.

These algorithms adaptively improve their performance as the number of available training samples grows. Deep learning is a specialized form of machine learning.

The field of Machine Learning is ushering in a new world where we "teach" computers to make decisions autonomously, allowing us to analyze data and accordingly improve or develop new products.

In the Machine Learning Fundamentals course, we will learn the basics of the field, understanding what artificial intelligence is.

We will then explore the history of developments and technological advancements, as well as the significant developments in recent years that have led to a sharp rise in the increasing use of artificial intelligence in various projects, such as medicine, security, autonomous transportation, finance, and more.

Machine Learning Fundamentals Course Content

?What is Machine Learning
History of Machine Learning
Supervised Learning
Overfitting and Underfitting
Evaluating Performance
Unsupervised Learning
Reinforcement Learning
Framing a Learning Problem

Talk to an Advisor

Alex Shoihat

Head of Machine Learning

Alex holds a bachelor's degree in Information Systems (B.Sc.) and a master's degree in Electrical and Electronics Engineering.

Alex is a Machine Learning Engineer at RT. He specializes in the AI field, with over 13 years of experience in project development, management, and transitioning from development to production in various domains such as Linux Embedded.

Alex has experience working with the integration of Machine Learning and Deep Learning in the Computer Vision and Data Analysis field.

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