Wavelabs Conducts Deep Learning Workshop In Association With MaLAI Club
An introduction to Deep Learning and hands-on experience in building models for use cases in real life
If you are a developer and are keen on understanding Deep Learning and how it can be helpful in solving the world’s most challenging problems, you are not alone. This is demonstrated by the increasing number of tech events, conferences and workshops being conducted across the globe, that explores Deep Learning and how it can be applied in different industries.
While Machine Learning (ML) has proven to solve real-world business problems, solutions based on Deep Learning are far more effective and ensures versatility of operation with implications that can go far beyond the capabilities of ML. Deep Learning as a subject, however, remains an important open research field. In fact, Wavelabs, in association with MaLAI Club has conducted several workshops where they explored the fundamentals of Deep Learning by training and deploying models and using the results to improve performance and capabilities.
The most recent event was conducted on 23rd February 2019 at Wavelabs. This was an in-person workshop that sought to teach the fundamentals of Deep Learning and how one can build and deploy a model through hands-on training in four hours. The session was delivered by Shashank Venkat, Deep Learning Specialist at Wavelabs with more than two years of experience in researching and working exclusively in the field. The workshop was free for all; students, architects, and developers.
The workshop started with a little history and the definition of Artificial Intelligence (AI). Evolving from the study of pattern recognition in AI, ML emerged as a subset that uses statistical strategies without being explicitly programmed for the purpose. Deep Learning, however, takes this to the next level. While ML tends to depend on feature engineering that needs to be performed manually, Deep Learning models gain far more insights into the data without any manual tinkering. The workshop then dwelled into the various applications of Deep Learning in today’s world and the problems that it seeks to solve.
After this, it discussed the mathematical foundations in building Deep Learning models. The workshop also demonstrated how Deep Learning is actually done, including the preparatory steps, the procedure, and the impact.
By the end of this workshop, the attendees had witnessed the effectiveness of Deep Learning and gained a deep intuitive understanding of the technology. The workshop also helped them build and deploy their first neural network.
It was an engaging and widely successful event. Since there were a lot of people in the same room curious about the same topic, it also led to great discussions and conversations.
“It was a great opportunity to both connect with new people and learn new things. I would really want to participate if they held more such workshops”, says