Artificial Intelligence is transforming industries by enabling machines to learn from data and make intelligent decisions. This course offers an in-depth exploration of Recurrent Neural Networks (RNN) and Deep Neural Networks (DNN), two pivotal AI technologies. You鈥檒l start with the basics of RNNs and their applications, followed by an examination of DNNs, including their architecture and implementation using PyTorch. You will master building and deploying sophisticated AI models, develop RNN models for tasks like speech recognition and machine translation, understand and implement DNN architectures, and utilize PyTorch for model building and optimization. By the end, you'll have a robust knowledge of RNNs and DNNs and the confidence to apply these techniques in real-world scenarios. Designed for data scientists, machine learning engineers, and AI enthusiasts with basic programming (preferably Python) and statistics knowledge, this course combines theory with practical application through video lectures, hands-on exercises, and real-world examples.
Focus of the Course
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Skills You'll Learn
Artificial Intelligence and Machine Learning (AI/ML), Artificial Neural Networks, PyTorch (Machine Learning Library), Deep Learning, Natural Language Processing, Data Science, Predictive Modeling, Applied Machine Learning, Machine Learning, Network Architecture, Artificial Intelligence, Python Programming, Application Deployment
From the lesson
Introduction
In this module, we will introduce you to the course instructor, providing insights into their background and expertise. Additionally, we will outline the primary focus and objectives of the course, setting the stage for your learning journey in AI sciences.
Taught By
Packt - Course Instructors