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September 21 through November 2, 2024. Six Saturdays 1:30-4:30pm (9/21, 9/28, 10/5, 10/19, 10/26, 11/2). The IEEE North Jersey Section Communications Society Chapter is offering a course entitled "DEEP LEARNING WITH APPLICATIONS". Deep learning is a transformative field within artificial intelligence and machine learning that has revolutionized our ability to solve complex problems in various domains, including computer vision, natural language processing, and reinforcement learning. This hands-on course on deep learning is designed to provide students with an understanding how these amazing successes are made possible by drawing inspiration from the way that brains, both human and otherwise, operate. Students will gain a comprehensive foundation in the principles, techniques, and applications of deep neural networks. Learning how to solve real data-set based applications will teach students how to really apply deep learning with Python programming software. Participants will be asked to design and train deep neural networks to perform tasks such as image classification using commonly available data sets. However, participants are encouraged to apply the techniques from this course to other data sets according to their interests. Discuss with the instructor in order to propose your own project. More importantly, this will set the foundations for understanding and developing Generative AI applications. The IEEE North Jersey Section's Communications Society Chapter can arrange for providing IEEE CEUs - Continuing Education Units (for a $5 charge) upon completion of the course. Course prices: $75 for Undergrad/Grad/Life/ComSoc members, $100 for IEEE members, $150 for non-IEEE members Co-sponsored by: Education Committee Speaker(s): Thomas Long, Agenda: 1. Introduction to Neural Networks: Explore the fundamental concepts of artificial neural networks, backpropagation, activation functions, and gradient descent, laying the groundwork for deep learning understanding. 2. Introduction to PyTorch: Learn how to implement and train neural networks using PyTorch one of the most popular deep learning frameworks. Understand tensors. 3. Computer Vision Applications: Apply deep learning to computer vision problems, including image classification and object detection using Convolutional Neural Networks (CNNs) 4. Training and Optimizing Deep Neural Networks: Study techniques for training deep neural networks effectively, including optimization algorithms, weight initialization, regularization, and dropout. 5. Sequential Data Analysis: Explore how deep learning is used to analyze sequential data using Recurrent Neural Networks (RNNs). In particular, explore how neural networks are used in Natural Language Processing (NLP) tasks such as sentiment analysis and machine translation. 6. Generative AI: Overview of generative ai techniques that leverage the patterns present in a dataset to generate new content. Applications of generative ai include large language models such as ChatGPT and image generation models such as Midjourney and Stable Diffusion. This course assumes a basic understanding of machine learning concepts and programming skills in Python. Familiarity with linear algebra and calculus will be beneficial, but not mandatory. Statistical software (Python, Scikit-learn) and Deep Learning Frameworks (Pytorch, TensorFlow) will be used throughout the course for the exploration of different learning algorithms and for the creation of appropriate graphics for analysis. Learning objectives: Subjects covered include these and other deep learning related materials: artificial neural networks, training deep neural networks, RNN, CNN, image recognition, natural language processing, GANs, data processing techniques, and NN architectures. The course is intended to be subdivided into 3-hour sessions. Each lecture is further subdivided into lecture, guided and independent project based exercises to build experience with hands-on techniques. This course will be held at FDU - Teaneck, NJ campus. Checks should NOT be mailed to this address. Can bring checks in person or use online payments at registration. Email the organizer for any questions about course, registration, or other issues. Technical Requirements: Students will need access to the Python programming language. In addition to a standard Python installation, most programming exercises will use the package Scikit-learn. Basic programming skills and some familiarity with the Python language are assummed. Students are expected to be able to bring a laptop onto which most of these libraries can be pre-installed using python's pip install. Most of the coding in this course will use the Python programming language. Coding examples and labs will be distributed in the form of Juypter notebooks. In addition to standard Python, most programming exercises will use either the PyTorch or TensorFlow libraries. Books and other resources will be referenced. Room: Room 306, Bldg: Becton Building , FDU Metropolitan Campus, 960 River Road, Teaneck, New Jersey, United States, 07666

The IEEE North Jersey Section is extremely proud to dedicate the new IEEE Neutrodyne Circuit Milestone. The Neutrodyne Circuit represents a critical development in the history of electronic circuits, known for its innovative design that minimized interference and improved the performance of radio receivers. It was invented in 1922 by Professor Louis Alan Hazeltine on the Stevens Institute of Technology campus. This milestone underscores the importance of technology that is both forward-thinking and grounded in sustainable practices. Please join us for the IEEE Milestone Dedication Ceremony. Date: 19 October 2024 Time: 12:00 PM to 2:00 PM (All times are US/Eastern) Location: Corcoran Room, The Gateway Academic Center (North), Stevens Institute of Technology Hoboken, New Jersey 07030 A detailed agenda and parking information will be posted soon Agenda: 12:00pm-2:00pm The Dedication Ceremony The detailed agenda will be posted soon. [] Room: Corcoran Room, Bldg:  The Gateway Academic Center (North),, 1 Castle Point Terrace, Hoboken, New Jersey, United States, 07030

The IEEE picnic will be held at TechWorks (321 Water Street, Binghamton, NY 13901) on Saturday, October 19, 2024 from 1 pm to 4 pm. Lunch will be provided by Smokey Legends BBQ. Each Chapter will be providing a poster session about their group and/or upcoming events. Reservations are required. All chapter chairs, please make sure that you have someone from your group available to present on upcoming events. A projector/screen will be available. Presentations will not be more than 5 minutes each. Agenda: TechWorks Tours from 1 pm to 4 pm. Lunch will be provided by Smokey Legends BBQ. TechWorks! is a Center initiative that showcases central New York State technology in action. TechWorks! is developing from the inside out - first ideas, then artifacts and events, in preparation for a world-class visitor destination where regional innovations past and present can inspire the future. At TechWorks!, celebrate regional ingenuity by flying Link pilot trainers and a Lockheed Martin helicopter trainer, viewing 3D images using a century of different technologies, playing a Link Nickelodeon, plus operating 1960s computer equipment built at IBM Plant # 1 in Endicott, NY. Techworks, 321 Water St. , Binghamton, New York, United States, 13901