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Event Features
- Covered fundamentals of Machine Learning (ML) and real-world applications
- Introduced Deep Learning (DL) concepts including CNNs and RNNs
- Explained core ML types: Supervised, Unsupervised, and Reinforcement Learning
- Demonstrated popular ML algorithms: Linear/Logistic Regression, Decision Trees, KNN, K-Means
- Walked through a complete ML pipeline: from data collection to deployment
- Explained LLMs (Large Language Models) and transformer architecture
- Mapped AI usage across major platforms: Facebook, WhatsApp, YouTube, TikTok, etc.
Event Description
Event FAQ
Anyone with an interest in Machine Learning and AI students, graduates, working professionals, or career changers is welcome.
The sessions are led by Santhana Krishnan, a seasoned expert in Machine Learning and Artificial Intelligence.
Basic programming knowledge is helpful, but not mandatory. The sessions are beginner-friendly and hands-on.
This event was conducted offline (in-person) at the BloomTusks Technologies.
Event Participants
Event Participants
Kabilan
Student
MaduraiI am a college student with a keen interest in exploring emerging technologies like Machine Learning and Generative AI.
Abishek
Student
MaduraiCollege student with a strong passion for learning new technology and exploring the latest trends in AI and Machine Learning.
Karunya
Software Engineer
MaduraiA tech enthusiast passionate about building innovative solutions and exploring emerging technologies in AI and development.
Hussain
Senior Software Engineer
MaduraiDriven professional with a knack for solving complex problems and staying ahead with emerging technologies.
Schedule
Registration opens for participants and attendees, followed by a welcome address by the organizers introducing the event.
A Journey into ML & DL introduced participants to the fascinating world of Artificial Intelligence, covering foundational concepts in Machine Learning and Deep Learning. It highlighted real-world applications, future opportunities, and inspired learners to explore AI-driven innovation with confidence.
Bridging Academia and Industry:
Speakers discussed the importance of hands-on learning and how academic programs can evolve to meet the demands of real-world AI projects.
Future Skills for AI Careers:
Panelists emphasized the need for critical thinking, continuous learning, and mastering tools like Python, TensorFlow, PyTorch, and cloud platforms.
Generative AI and LLMs in Daily Life:
Experts explained how tools like ChatGPT, DALL·E, and other LLMs are redefining creativity, automation, and education.
Overview: Tailored for students and professionals looking to transition into AI roles.
Focus Areas:
Role of certifications and MOOCs
Building a strong portfolio
Resume and interview prep for AI/Machine Learning roles
Panel Guests: Industry experts shared their journeys and hiring insights.
Overview: Participants worked in groups to solve real industry problems using ML.
Domains Covered:
Healthcare diagnosis prediction.
Retail recommendation engines.
Finance fraud detection.
Manufacturing quality inspection using CNNs.
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