We are excited to present a brand new workshop –– Introduction to Machine Learning! Machine learning is a data analysis technique that automates the creation of analytical models. It is a subfield of artificial intelligence predicated on the premise that systems can learn from data, spot patterns, and make choices with little or no human interaction. Image and audio recognition, natural language processing, and forecasting are all examples of machine learning applications. Over the course of the workshop, students will learn about the key concepts and techniques used in these fields, including computer science, data mining, and natural language processing. In addition to gaining a strong theoretical understanding of these topics, students will be able to:
Machine learning is an artificial intelligence subject that entails teaching computer systems to learn from data and make predictions or judgments without being explicitly programmed. The basic idea is to give the machine access to data and let it know from it. Machine learning is classified into three types: supervised learning, unsupervised learning, and reinforcement learning. Supervised learning includes labeled data to train the computer, unsupervised learning involves enabling the system to detect patterns in the data on its own, and reinforcement learning involves trial and error to train the machine. Linear regression, decision trees, and k-nearest neighbors are examples of fundamental approaches. In-depth explanations of these concepts will be explained in the workshop.
Arin Kadakia, our instructor for this workshop, has designed this workshop for intermediate coders to follow through. “This workshop will provide students with the basics of what machine learning is and how it is prevalent in society. I will walk them through the code line by line to make sure they understand every part and so that they can implement more advanced models in the future,” he expressed. Arin also states that students "will understand the different models that can be built and construct both a basic linear and polynomial regression model.” There are several concepts that will be highlighted in this workshop, including data mining, natural language processing, and computer science. Data mining is the process of identifying patterns and information in massive amounts of data. Techniques including clustering, association rule mining, and classification are used. These approaches and technologies enable computers to absorb and comprehend human language, and then make judgments based on that comprehension. Using these techniques, our instructors will teach algorithms and a simple game that students can follow and recreate.
Machine learning is crucial to learn because it allows us to teach computer systems to improve their performance automatically as they gain experience. This has several potential uses in healthcare, banking, transportation, and industry. Machine learning also enables the development of intelligent systems capable of adapting to changing surroundings and learning from their failures. This might lead to self-driving vehicles and better medical diagnosis. Furthermore, machine learning is a fast-emerging field. It is expected to grow significantly as a career and in the job market in the next 10 years. It’s a valuable skill to have at hand, especially since many industries are now incorporating machine learning to improve their operations and processes.
The workshop will be held on 2/4/2023 and 4/15/2023, both from 10 am to 11:30 am PST. This workshop requires basic knowledge of Python and computers. As always, it is completely free of charge. If you’re interested, sign up here.
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