| Participated in DataHour: LLM Fine-tuning for Beginners with Unsloth |
| Participated in DataHour: Large Language Models: Foundation, Evolution and Applications |
| Participated in DataHour: Introduction to Serving Machine Learning Models as Microservices |
| Participated in DataHour: Innovative Applications of Artificial Intelligence |
| Participated in DataHour: Real-World REST APIs with Docker Containers |
| Participated in DataHour: Building Robust RAG Applications for the Real-World |
| Participated in DataHour: Evaluating LLMs and LLM Systems : Pragmatic Approach |
| Participated in DataHour: Rust and Python in the age of LLMOps |
| Participated in DataHour: Full-Stack Data Science with FastAPI |
| Participated in Better Data Understanding Through GenAI Powered Search |
| Participated in JanataHack: Demand Forecasting |
| Participated in DataHour: Empowering Stakeholders: With Supercharged & Functional Tableau Dashboard |
| Participated in DataHour: Responsible Use of Generative AI |
| Participated in DataHour: Creating Delightful Customer Experience with RAG |
| Participated in DataHour: The Future of GenAI |
| Participated in HackLive 3: Guided Hackathon - NLP |
| Participated in JanataHack: NLP Hackathon |
| Participated in JanataHack: Time Series Forecasting |
| Participated in DataHour: Data Curation and Reliability for LLM and GenAI Applications |
| Participated in DataHour: Should I Use RAG or Fine-Tuning? |
| Participated in DataHour: How to Customize and Evaluate Your LLMs |
| Participated in DataHour: Natural Language to SQL Translation: The Challenges, Evolution and Future |
| Participated in DataHour:LangChain 101 |
| Participated in DataHour: Building Generative AI Applications using Amazon Bedrock |
| Participated in DataHour: Demystifying HugginFace, LlamaIndex, and LangChain |
| Participated in DataHour: Enterprise Challenges with Generative AI and LLMs |
| Participated in DataHour: ML Model Deployment: Best MLOps and GitOps Practices |
| Participated in DataHour: Open-Source For Accelerating AI Development |
| Participated in DataHour: Implementing Gen AI solutions with RAG Architecture |
| Participated in DataHour: Predictive Analytics - Performance Estimation without the Target Data |
| Participated in DataHour: Build Your Own Private ChatBot using GenAI- RAG |
| Participated in DataHour: Relationship of ML and Statistics - Optimizing Algorithmic Functions |
| Participated in DataHour: Natural Language to SQL: Analyzing Netflix Movies with LLMs |
| Participated in DataHour: Search With ChatGPT: RAG and Semantic Search |
| Participated in DataHour: Mastering Conversational AI: Building Question-Answer Bot with LLM and RAG |
| Participated in DataHour: Creating Synthetic Data: An Easy Python Tutorial for Beginners |
| Participated in DataHour: Interpreting Machine Learning Models with Python |
| Participated in DataHour: Significance of Vector Databases in Gen AI |
| Participated in DataHour: Model Explainability and Model Diagnosis |
| Participated in DataHour: Large Language Models for India |
| Participated in DataHour: Introduction to Convolutional Neural Networks |
| Participated in DataHour: Visualizing Insights: Understanding Data Visualization Techniques |
| Participated in DataHour: Creating Advanced & Large-Scale Recommendation System |
| Participated in DataHour: Building a Simple LLM Application: ChatGPT Summarizer |
| Participated in DataHour: Building Safe AI Experiences with Azure AI Content Safety |
| Participated in DataHour: Fighting Customer Churn with Data Science, Analytics & Machine Learning |
| Participated in DataHour: End-to-End Development: LLMOps and Azure AI for Generative Apps |
| Participated in DataHour: Crafting and Implementing a GenAI Strategy with StratOps |
| Participated in DataHour: ML Based Manufacturing Quality Inspection |
| Participated in DataHour: Generative AI / LLMs using Databricks Data Intelligence Platform |
| Participated in DataHour: Introduction to Time Series Analysis |
| Participated in DataHour: Keeping LLMs Relevant: A Practical Guide to RAG and Fine-tuning |
| Participated in DataHour: Navigating the Maze of A/B Testing Pitfalls in Business Decision Making |
| Participated in DataHour: LLMOps - MLOps for Generative AI |
| Participated in DataHour: Harnessing LLMs: Exploring Controllable Text Generation Without Fine-Tuning |
| Participated in DataHour: Custom GPTs in Industry: Assessing GPT-4V |
| Participated in DataHour: LLMs in Action: Crafting a Winning Product Strategy |
| Participated in DataHour: Large Language Models- Evolution, Challenges and Way Forward |
| Participated in DataHour: Multi-Modal RAG and Evaluation with LlamaIndex |
| Participated in DataHour: NoSQL: Leveraging Large Language Models for Text2SQL |
| Participated in Game of Deep Learning: Computer Vision Hackathon and secured rank 49 |
| Participated in DataHour: Optimizing LLMs with Retrieval Augmented Generation and Haystack 2.0 |
| Participated in DataHour: High Impact AI/ML Solutions by Effective Formulation |
| Participated in DataHour: Democratising AI Deployment |
| Participated in AmExpert 2019 – Machine Learning Hackathon and secured rank 589 |
| Participated in DataHour: LLM Training Tips & Tricks |
| Participated in DataHour: MemeGPT: Fine-Tuning LLMs to Generate Memes |
| Participated in DataHour: Current and Best Practices for LLM Evaluation |
| Participated in DataHour: Medical-Chat Bot: The History of Our Attempt |
| Participated in DataHour: Elevating Business Transformation: Leveraging Retrieval Augmented Generation (RAG) |
| Participated in DataHour: Building Useful Applications with LLMs |
| Participated in DataHour: Create a Language to SQL Translator with LLM |
| Participated in DataHour: Overview of Latent Diffusion, Stable Diffusion 1.5, & Challenges with SD 1.5 |
| Participated in DataHour: Era of AI-Assisted Innovation |
| Participated in DataHour: Production Stack for LLMs |
| Participated in DataHour: Building Multi-Stage Reasoning Systems with LangChain |
| Participated in DataHour: Securing LLM-Based Applications |
| Participated in India ML Hiring Hackathon 2019 and secured rank 596 |
| Participated in DataHour: BUILDING CHATBOTS USING LLM |
| Participated in DataHour: The Generative AI, Good & Bad with Real World Examples |
| Participated in DataHour: NLP Tasks Chaining with GenAI: How to Utilize Traditional NLP Knowledge in the World of LLMs? |
| Participated in DataHour: LLMs and Foundational Models in Ads Personalization |
| Participated in DataHour: Harnessing the Power of LLMs: A Deep Dive into Practical Solutions |
| Participated in DataHour: Business Intelligence with Microsoft Power BI |
| Participated in DataHour: Building Complex Systems Using ChatGPT |
| Participated in DataHour: The Dangers of Dirty Data |
| Participated in DataHour: Advanced Generative AI and Data Storytelling |
| Participated in DataHour: The 3 Secrets to Giving a Great Data Presentation |
| Participated in DataHour: Crash Course on Data Visualization with Power BI |
| Participated in DataHour: Generative AI: The Responsible Path Forward |
| Participated in DataHour: Chat With Your Data- Dive into GPT Langchain LLM Framework |
| Participated in DataHour: Efficient Fine-Tuning of LLMs on single T4 GPU using Ludwig |
| Participated in DataHour: From Text to Video: Unraveling the Power and Pitfalls of Generative AI |
| Participated in DataHour: Unleashing Generative AI in Data Analytics |
| Participated in DataHour: The Ethical Frontiers of Generative AI |
| Participated in DataHour: Crafting Text-Based Conversations: Leveraging VertexAI, Langchain, and Streamlit |
| Participated in DataHour: How to Build a Generative AI Application? |
| Participated in DataHour: Applications of Data Science in Pricing |
| Participated in DataHour: Explainable AI: Demystifying the Black Box Models |
| Participated in DataHour: RAG to Reduce LLM Hallucination |
| Participated in DataHour: Demystifying Computer Vision |
| Participated in DataHour: Using Clinical Data Science to Improve Clinical Outcomes |
| Participated in DataHour: How LLMs Can Be Used in Day-to-Day Developer Tasks |
| Participated in DataHour: Azure Bot Services: Transforming Conversational AI for Enhanced Experiences |
| Participated in DataHour: Supercharging LLM API Development with Fast API |
| Participated in DataHour: The Future of Autonomous Systems and How Humans Fit In |
| Participated in DataHour: Generative AI- Training Pipelines and Advanced Strategies |
| Participated in DataHour: Era of Gen AI |
| Participated in DataHour: Exploring Limitless Potential: Leveraging Retrieval Augmented Generations with LLMs |
| Participated in DataHour: Master the Art of Prompting with Generative AI for Real-World Business Solutions |
| Participated in DataHour: Diffusion Model Fundamentals and Various Applications |
| Participated in DataHour: Exploring Extended Reality- Going Beyond the Basics |
| Participated in DataHour: Exploring the Potential of Generative AI |
| Participated in DataHour: Attention From Scratch |
| Participated in DataHour: Mastering Sentiment Analysis through Generative AI: A Deep Dive |
| Participated in DataHour: Dreambooth- Stable Diffusion for Custom Images |
| Participated in DataHour: Training Your Own LLM Without Coding |
| Participated in DataHour: Introduction of Microsoft Fabric |
| Participated in DataHour: Application of Data Science in the world of FinTech |
| Participated in DataHour: LLM Fine Tuning with PEFT Techniques |
| Participated in DataHour: Cutting Edge Tricks of Applying Large Language Models |
| Participated in DataHour: Evaluation of GenAI Models and Search Use Case |
| Participated in DataHour: Building Large Language Models for Code |
| Participated in DataHour: Quantum Computing Applications in Financial Industry |
| Participated in DataHour: Practical Guide to Train Your Own Large Language Models |
| Participated in DataHour: Using Langchain with LLM |
| Participated in DataHour: Paying Attention to Attention - A Deep Dive into Attention Models |
| Participated in DataHour: GEN AI - Image to Image Generation |
| Participated in DataHour: Unlocking Language Model Potential - The Power of Prompt Engineering |
| Participated in DataHour: Introduction to LLMs: An Interactive Workshop |
| Participated in GANs- Explore the Boundaries of Generative Art |
| Participated in LangChain in Action: Crafting Innovative LLM Powered Applications |
| Participated in DataHour: Generative AI with LLMs |
| Participated in DataHour: Building Trust, Ethics and Privacy in Generative AI & LLM |
| Participated in DataHour: Fine Tuning Generative Models |
| Participated in Practice Problem: Intel Scene Classification Challenge |
| Participated in McKinsey Analytics Online Hackathon- Recommendation Design |
| Participated in Time Series Forecasting |
| Participated in Black Friday Sales Prediction |
| Participated in Twitter Sentiment Analysis |
| Participated in The Convergence of BIG DATA and Machine Learning (Pune Meetup) |
| Participated in ML Hikeathon (An Online Machine Learning Hackathon) |
| Participated in Club Mahindra DataOlympics |
| Participated in Identify the Sentiments |
| Participated in LTFS Data Science FinHack ( ML Hackathon) |
| Participated in Analytics Vidhya Internship Challenge |
| Participated in Big Mart Sales Prediction |
| Participated in WNS Analytics Wizard 2019 |
| Participated in Webinar: Getting Started with Recommendation Engines |
| Participated in Loan Prediction |
| Participated in LTFS Data Science FinHack 2 |
| Participated in Janatahack: Healthcare Analytics |
| Participated in JanataHack: Recommendation Systems |
| Participated in Janatahack: Healthcare Analytics II |
| Participated in Janatahack: Cross-sell Prediction |
| Participated in Janatahack: Customer Segmentation |
| Participated in Janatahack: Machine Learning in Agriculture |
| Participated in Janatahack: Independence Day 2020 ML Hackathon |
| Participated in LTFS Data Science FinHack 3 |
