Hands-On Workshop On Neutral Networks and Deep Learning

The first day of the workshop began with a warm welcome from Tanisha Agarwal. She set a positive tone for the event, making everyone feel comfortable and excited about the days ahead. The day kicked off with a Q&A session where students had the opportunity to delve into the differences between Deep Learning and Machine Learning. This interactive session allowed students to ask questions and clarify their doubts, making the concepts clearer.

Following the Q&A, students participated in hands-on activities focused on understanding Neural Networks. These activities were designed to be engaging and educational, helping students grasp the fundamental concepts of Neural Networks through practical experience. The day concluded with insightful discussions on the various applications of Neural Networks in different fields. Additionally, there were informative sessions on the differences between CPU and GPU, the role of APIs in programming, and the importance of threads in executing multiple tasks simultaneously.

The discussions on CPU vs. GPU were particularly enlightening, as students learned about the specific advantages of each type of processor. They discovered that while CPUs are versatile and capable of handling a wide range of tasks, GPUs are specialized for parallel processing, making them ideal for tasks such as training deep learning models. The session on APIs provided students with a deeper understanding of how different software components interact with each other, which is crucial for developing efficient and scalable applications. The explanation of threads helped students appreciate the importance of concurrency in programming, enabling them to write more efficient code that can handle multiple tasks at once.

Day 2 – 23/08

The second day was dedicated to Excel Optimization using the Solver tool, taught by Mr. Bastin Robins. He began by explaining the basics of optimization and how the Solver tool can be used to find optimal solutions for various problems. Each student was then asked to think of an application where this optimization technique could be applied, encouraging them to connect the theory with real-world scenarios.

Mr. Robins also shared valuable insights into what industries expect from students entering the workforce. He emphasized the importance of practical knowledge and problem-solving skills, which are highly valued by employers. This session provided students with a clearer understanding of how to apply their knowledge in professional settings and what skills they need to develop to meet industry standards.

During the session, students learned how to set up and solve optimization problems in Excel, using the Solver tool to find the best solutions. They explored various applications of optimization, such as minimizing costs, maximizing profits, and improving efficiency in different industries. Mr. Robin’s practical approach helped students see the relevance of optimization techniques in real-world scenarios, making the learning experience more meaningful and engaging.

Day 3 – 24/08

The final day of the workshop was again led by Mr. Bastin Robins, who focused on teaching logistic regression and linear regression through manually written code. He explained each step of the code in detail and demonstrated how to execute it. Students were then given the opportunity to replicate the code and run it on a dataset, reinforcing their understanding through practice.

Mr. Robins also presented an industry scenario to the students, illustrating how these regression techniques are used in real-world applications. This practical example helped students see the relevance of what they were learning and how it could be applied in their future careers. At the end of the session, Mr. Robins encouraged students to continue exploring the field of data science and to ensure they have a strong grasp of the basic concepts.

The event concluded with a vote of thanks from Leran Antony, who expressed gratitude to all the speakers and participants for making the workshop a success. This marked the end of a highly informative and engaging series of sessions, leaving students motivated and better equipped with knowledge and skills in data science.