Flowers

DataHour: Introduction to Multi-Modal Machine Learning

Online 28-03-2023 08:30 PM to 28-03-2023 09:30 PM
  • 7836

    Registered

  • Knowledge and Learning.

    Prizes

Due to health issues of the speaker this session has been cancelled.

 

About the DataHour:

Multi-Modal Machine Learning refers to the technique of combining data from multiple sources, such as images and text, to build predictive models. This approach enables the model to learn from different types of data and capture more complex relationships between them.

An example of multi-modal machine learning is Vision+Language, where the model is trained on both visual data and textual data simultaneously. This can be useful for tasks such as image captioning, where the model needs to understand the content of an image and generate a descriptive caption.

For example, suppose you want to build a system that can describe a picture of a dog. A Multi-Modal Machine Learning Model would be trained on both the image of the dog and a textual description of the dog, such as "a fluffy golden retriever running in a park." The model would then learn to associate visual features of the dog, such as its shape and color, with specific words and phrases in the textual description.

This type of multi-modal machine learning can be challenging because it requires integrating data from different modalities and learning to map between them. However, it can also be highly effective because it allows the model to capture richer and more nuanced relationships between different types of data.

In this Datahour, Prabakaran will teach you the fundamentals of Multimodal Machine Learning with a hands-on example.


Prerequisites:
 
A strong interest in Data Science


Who is this DataHour for?

  • Students & Freshers who want to build a career in the Data-tech domain.
  • Working professionals who want to transition to the Data-tech domain.
  • Data science professionals who want to accelerate their career growth


Note:
E-certificates will be provided within 24 - 48 hours of the session only to those who have attended the entire webinar. Please make sure to join the zoom webinar with your correct name and email address to ensure that your certificate is properly credited to you.


Speaker:

Prabakaran Chandran

Data Scientist II at Captain Fresh

Prabakaran is an Engineering Graduate (Instrumentation and Control Engineering) with the area of specialization Computational Intelligence currently working as a Data Scientist in Mu Sigma, a leading problem-solving company since 2019. He always wants to be in the active learning curve. He is an ICE graduate and working as a Data Scientist. As a Data Scientist, he is proficient in Advanced Analytics, Statistics, Python, R, SQL. He has been working on projects which have created a huge impact on business using AI and Data Science. He has been a part of 2 members team to build AI-based solutions for fortune 500 firms in the area of Computer Vision, Natural Language Processing and Deep learning. He has experience in Analytics and Machine learning Application development with the use of Analytics and Development frameworks. As a young and passionate Data Scientist, he has been mentoring colleges and students in AI, DS projects, and ideas. He has taken nearly 10 Webinars and Seminars on Deep learning, Computer Vision, and Data Science.

Connect with him on Linkedin

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