Participated in
LTFS Data Science FinHack 2
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Participated in
Data Science Hackathon: Churn Prediction
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Participated in
ABInBev : Data Science Talent Hunt Hackathon
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Participated in
McKinsey Analytics Online Hackathon - Sales Excellence
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Participated in
AmExpert 2018 (Machine Learning Hackathon)
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Participated in
Game of Deep Learning: Computer Vision Hackathon
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Participated in
WNS Analytics Wizard 2019
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Participated in
Click Prediction Hackathon
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Participated in
WNS Analytics Wizard 2018 (Machine Learning Hackathon)
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Participated in
Data Science Hackathon - Cross-sell: target the right customer
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Participated in
Capillary Machine Learning Hackathon
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Participated in
LTFS Data Science FinHack ( ML Hackathon)
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Participated in
Club Mahindra DataOlympics
|
Participated in
Felicity : Kings of Machine Learning
|
Participated in
Genpact Machine Learning Hackathon
|
Participated in
McKinsey Analytics Online Hackathon- Recommendation Design
|
Participated in
ML Hikeathon (An Online Machine Learning Hackathon)
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Participated in
Enigma codeFest Machine Learning
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Participated in
DataHour: LLM Fine-tuning for Beginners with Unsloth
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Participated in
DataHour: Large Language Models: Foundation, Evolution and Applications
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Participated in
DataHour: Introduction to Serving Machine Learning Models as Microservices
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Participated in
DataHour: Innovative Applications of Artificial Intelligence
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Participated in
DataHour: Real-World REST APIs with Docker Containers
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Participated in
DataHour: Building Robust RAG Applications for the Real-World
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Participated in
DataHour: Evaluating LLMs and LLM Systems : Pragmatic Approach
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Participated in
DataHour: Continuous Testing and Evaluation with LLMs
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Participated in
DataHour: Rust and Python in the age of LLMOps
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Participated in
DataHour: Full-Stack Data Science with FastAPI
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Participated in
Better Data Understanding Through GenAI Powered Search
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Participated in
DataHour: Harnessing ML and NLP for Elevated Customer Experiences
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Participated in
DataHour: Empowering Stakeholders: With Supercharged & Functional Tableau Dashboard
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Participated in
DataHour: Responsible Use of Generative AI
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Participated in
DataHour: Creating Delightful Customer Experience with RAG
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Participated in
DataHour: The Future of GenAI
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Participated in
DataHour: Data Curation and Reliability for LLM and GenAI Applications
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Participated in
DataHour: Should I Use RAG or Fine-Tuning?
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Participated in
DataHour: How to Customize and Evaluate Your LLMs
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Participated in
DataHour: Natural Language to SQL Translation: The Challenges, Evolution and Future
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Participated in
DataHour:LangChain 101
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Participated in
DataHour: Building Generative AI Applications using Amazon Bedrock
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Participated in
DataHour: Demystifying HugginFace, LlamaIndex, and LangChain
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Participated in
DataHour: Enterprise Challenges with Generative AI and LLMs
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Participated in
DataHour: ML Model Deployment: Best MLOps and GitOps Practices
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Participated in
DataHour: Open-Source For Accelerating AI Development
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Participated in
DataHour: Implementing Gen AI solutions with RAG Architecture
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Participated in
DataHour: Predictive Analytics - Performance Estimation without the Target Data
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Participated in
DataHour: Build Your Own Private ChatBot using GenAI- RAG
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Participated in
DataHour: Relationship of ML and Statistics - Optimizing Algorithmic Functions
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Participated in
DataHour: Natural Language to SQL: Analyzing Netflix Movies with LLMs
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Participated in
DataHour: Search With ChatGPT: RAG and Semantic Search
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Participated in
DataHour: Mastering Conversational AI: Building Question-Answer Bot with LLM and RAG
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Participated in
DataHour: Creating Synthetic Data: An Easy Python Tutorial for Beginners
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Participated in
DataHour: Interpreting Machine Learning Models with Python
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Participated in
DataHour: Significance of Vector Databases in Gen AI
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Participated in
DataHour: Model Explainability and Model Diagnosis
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Participated in
DataHour: Large Language Models for India
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Participated in
DataHour: Introduction to Convolutional Neural Networks
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Participated in
DataHour: Visualizing Insights: Understanding Data Visualization Techniques
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Participated in
DataHour: Creating Advanced & Large-Scale Recommendation System
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Participated in
DataHour: Building a Simple LLM Application: ChatGPT Summarizer
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Participated in
DataHour: Building Safe AI Experiences with Azure AI Content Safety
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Participated in
DataHour: Fighting Customer Churn with Data Science, Analytics & Machine Learning
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Participated in
DataHour: End-to-End Development: LLMOps and Azure AI for Generative Apps
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Participated in
DataHour: Crafting and Implementing a GenAI Strategy with StratOps
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Participated in
DataHour: ML Based Manufacturing Quality Inspection
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Participated in
DataHour: Generative AI / LLMs using Databricks Data Intelligence Platform
|
Participated in
DataHour: Introduction to Time Series Analysis
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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
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Participated in
DataHour: LLMOps - MLOps for Generative AI
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Participated in
DataHour: Harnessing LLMs: Exploring Controllable Text Generation Without Fine-Tuning
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Participated in
DataHour: Custom GPTs in Industry: Assessing GPT-4V
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Participated in
DataHour: LLMs in Action: Crafting a Winning Product Strategy
|
Participated in
Ripik.AI HackFest: Unleashing AI Potential
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Participated in
DataHour: Large Language Models- Evolution, Challenges and Way Forward
|
Participated in
DataHour: Multi-Modal RAG and Evaluation with LlamaIndex
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Participated in
DataHour: NoSQL: Leveraging Large Language Models for Text2SQL
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Participated in
DataHour: Optimizing LLMs with Retrieval Augmented Generation and Haystack 2.0
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Participated in
DataHour: High Impact AI/ML Solutions by Effective Formulation
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Participated in
DataHour: Democratising AI Deployment
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Participated in
DataHour: Demystifying Demand Forecasting for Retail Success
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Participated in
DataHour: LLM Training Tips & Tricks
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Participated in
DataHour: Unwritten Rules for Success in Machine Learning
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Participated in
DataHour: Why Did My AI Do That? Decoding Decision-Making in ML
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Participated in
DataHour: MemeGPT: Fine-Tuning LLMs to Generate Memes
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Participated in
DataHour: Current and Best Practices for LLM Evaluation
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Participated in
DataHour: Medical-Chat Bot: The History of Our Attempt
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Participated in
DataHour: Machine Learning Tips and Tricks
|
Participated in
DataHour: Elevating Business Transformation: Leveraging Retrieval Augmented Generation (RAG)
|
Participated in
DataHour: Building Useful Applications with LLMs
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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
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Participated in
DataHour: Era of AI-Assisted Innovation
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Participated in
DataHour: Production Stack for LLMs
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Participated in
DataHour: Building Multi-Stage Reasoning Systems with LangChain
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Participated in
DataHour: Securing LLM-Based Applications
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Participated in
DataHour: BUILDING CHATBOTS USING LLM
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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?
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Participated in
DataHour: LLMs and Foundational Models in Ads Personalization
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Participated in
DataHour: Harnessing the Power of LLMs: A Deep Dive into Practical Solutions
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Participated in
DataHour: Business Intelligence with Microsoft Power BI
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Participated in
DataHour: Building Complex Systems Using ChatGPT
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Participated in
DataHour: The Dangers of Dirty Data
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Participated in
DataHour: Advanced Generative AI and Data Storytelling
|
Participated in
DataHour: The 3 Secrets to Giving a Great Data Presentation
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Participated in
DataHour: Crash Course on Data Visualization with Power BI
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Participated in
DataHour: Generative AI: The Responsible Path Forward
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Participated in
DataHour: Chat With Your Data- Dive into GPT Langchain LLM Framework
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Participated in
DataHour: Efficient Fine-Tuning of LLMs on single T4 GPU using Ludwig
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Participated in
DataHour: From Text to Video: Unraveling the Power and Pitfalls of Generative AI
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Participated in
DataHour: Unleashing Generative AI in Data Analytics
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Participated in
DataHour: The Ethical Frontiers of Generative AI
|
Participated in
DataHour: Crafting Text-Based Conversations: Leveraging VertexAI, Langchain, and Streamlit
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Participated in
DataHour: How to Build a Generative AI Application?
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Participated in
DataHour: Applications of Data Science in Pricing
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Participated in
DataHour: Explainable AI: Demystifying the Black Box Models
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Participated in
DataHour: RAG to Reduce LLM Hallucination
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Participated in
DataHour: Demystifying Computer Vision
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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
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Participated in
DataHour: Azure Bot Services: Transforming Conversational AI for Enhanced Experiences
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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
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Participated in
DataHour: Exploring Limitless Potential: Leveraging Retrieval Augmented Generations with LLMs
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Participated in
DataHour: Master the Art of Prompting with Generative AI for Real-World Business Solutions
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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
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Participated in
DataHour: Attention From Scratch
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Participated in
DataHour: Mastering Sentiment Analysis through Generative AI: A Deep Dive
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Participated in
DataHour: Dreambooth- Stable Diffusion for Custom Images
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Participated in
DataHour: Training Your Own LLM Without Coding
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Participated in
DataHour: Introduction of Microsoft Fabric
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Participated in
DataHour: Application of Data Science in the world of FinTech
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Participated in
DataHour: LLM Fine Tuning with PEFT Techniques
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Participated in
DataHour: Cutting Edge Tricks of Applying Large Language Models
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Participated in
DataHour: Evaluation of GenAI Models and Search Use Case
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Participated in
DataHour: Building Large Language Models for Code
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Participated in
DataHour: From APIs to Insights: Building Custom Power BI Connectors for RESTful APIs
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Participated in
DataHour: Quantum Computing Applications in Financial Industry
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Participated in
DataHour: Practical Guide to Train Your Own Large Language Models
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Participated in
DataHour: Using Langchain with LLM
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Participated in
DataHour: Paying Attention to Attention - A Deep Dive into Attention Models
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Participated in
DataHour: GEN AI - Image to Image Generation
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Participated in
DataHour: Unlocking Language Model Potential - The Power of Prompt Engineering
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Participated in
DataHour: Introduction to LLMs: An Interactive Workshop
|
Participated in
GANs- Explore the Boundaries of Generative Art
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Participated in
LangChain in Action: Crafting Innovative LLM Powered Applications
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Participated in
DataHour: Generative AI with LLMs
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Participated in
DataHour: Building Trust, Ethics and Privacy in Generative AI & LLM
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Participated in
DataHour: Fine Tuning Generative Models
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Participated in
DataHour: Generative AI using Azure Open AI
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Participated in
DataHour: Generative AI - Midjourney, Code Generation & Beyond
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Participated in
DataHour: Reducing chatGPT Hallucinations by 80%
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Participated in
DataHour: Building Bridges - The Art of Prompt Engineering
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Participated in
DataHour: LlamaIndex - QA Systems with Private Data and Effective Evaluation
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Participated in
DataHour: Handling Satellite and Geospatial Raster Data in Python
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Participated in
DataHour: Titanic Machine Learning Case Study using Python
|
Participated in
DataHour: Statistics with Python for Data Science
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Participated in
DataHour: ChatGPT in Python for Beginners
|
Participated in
DataHour: An Overview of Generative AI
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Participated in
DataHour: Exploring Dimensionality Reduction
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Participated in
DataHour: Generative AI and Large Language Models
|
Participated in
DataHour: Building an End to End Machine Learning Pipeline for Large Language Models (LLMs)
|
Participated in
DataHour: Web Scraping using Python Libraries
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Participated in
DataHour: Fine Tuning NLP Pipeline on Hugging Face
|
Participated in
DataHour: A Beginner's Guide to Natural Language Processing
|
Participated in
DataHour: An Overview of Named Entity Recognition(NER)
|
Participated in
DataHour: Introduction to Social Network Analysis
|
Participated in
DataHour: Understanding Logistic Regression and Decision Tree Analysis
|
Participated in
DataHour: Building an End-to-End Solution for Big Mart Sales Prediction
|
Participated in
DataHour: An Introduction to Machine Learning with Sequence Data
|
Participated in
DataHour: FIFA World Cup Match Analysis Using Python
|
Participated in
DataHour: Getting Started with Python
|
Participated in
DataHour: Generating Labeled Data through Weak Supervision
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Participated in
DataHour: Feature Engineering and Selection for Machine Learning
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Participated in
DataHour: Best of Pandas & The Power of Simple Models
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Participated in
DataHour: Conversational Intelligence & Interactive Bots
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Participated in
DataHour: Transformers from Scratch
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Participated in
DataHour: Machine Learning on Live Streaming Data for AIOps
|
Participated in
DataHour: Evaluation Criteria for Validating Machine Learning Models
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Participated in
DataHour: Forecasting & Time-series Analysis
|
Participated in
DataHour: An Introduction to POS Tagging and Hidden Markov Model
|
Participated in
DataHour: Boosting Performance with Ensemble Methods
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Participated in
DataHour: Feature Engineering and benefits of EDA
|
Participated in
DataHour: Constructing Machine Learning Pipelines using Scikit-learn
|
Participated in
DataHour: Document Segmentation using Layout Parser
|
Participated in
DataHour: Transforming HR with People Analytics
|
Participated in
DataHour: Application of ML Classification Techniques in Banking Industry
|
Participated in
DataHour: How to Forecast New Product Launches using Data Centric Approach
|
Participated in
DataHour: The Art of Using GPT3 Power
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Participated in
DataHour: Everything You Need to Know About Pandas
|
Participated in
DataHour: Text Classification for Beginners
|
Participated in
DataHour: Data Preparation and Feature Engineering in ML
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Participated in
DataHour: Unlocking the Power of Embeddings
|
Participated in
DataHour: A/B testing - Theory, Practice and Pitfalls
|
Participated in
DataHour: Understanding Graph Data Science
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Participated in
DataHour: Dealing with Imbalanced Datasets in ML Classification Problems
|
Participated in
DataHour: Salary Analysis and Prediction Using ML
|
Participated in
DataHour: Data Wrangling Using Geospatial Data in Python
|
Participated in
DataHour: Advanced Resume Shortlisting using NLP
|
Participated in
DataHour: Diabetic Patients’ Readmission Prediction using ML
|
Participated in
DataHour: No-code ML Hands-on using Orange Data Mining Tool
|
Participated in
DataHour: Deep Dive into Semantic Segmentation- Techniques, Challenges and State-of-the-Art
|
Participated in
Identify the Digits (MNIST)
|
Participated in
DataHack Premier League 2018
|
Participated in
Lord of the Machines: Data Science Hackathon
|
Participated in
Data Hack Round 1: Online Quiz (Nirvahana, By iQ’oniQ, NMIMS Hyderabad)
|
Participated in
Innoplexus Online Hackathon: Machine Learning Challenge
|
Participated in
New Frontiers In Deep Learning, (Meetup: Bangalore)
|
Participated in
Black Friday Sales Prediction
|
Participated in
Innoplexus Online Hiring Hackathon: Saving lives with AI
|
Participated in
Food Demand Forecasting
|
Participated in
McKinsey Analytics Online Hackathon
|
Participated in
QuantumBlack Hackathon
|
Participated in
AmExpert 2019 – Machine Learning Hackathon
|
Participated in
Loan Prediction
|
Participated in
HR Analytics
|
Participated in
Predict Number of Upvotes
|
Participated in
McKinsey Analytics Online Hackathon
|
Participated in
LTFS Data Science FinHack 3
|
Participated in
DataHour: Think like a Data Scientist
|
Participated in
Time Series Forecasting
|
Participated in
Big Break in Big Data: Sapient Talent Hunt for Data Engineers
|
Participated in
DataHour: Deploying Deep Learning model to production using FastAPI & Docker
|
Participated in
DataHour: Improving Search Results with Semantic Search
|
Participated in
DataHour: Efficient Implementations of Transformers
|
Participated in
DataHour: Introduction to Network Science
|
Participated in
DataHour: ML oops to MLOps!
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Participated in
DataHour: Data to Insightful Actions with No Code AI
|
Participated in
DataHour: SQL- One of the Key Ingredients for Data Science
|
Participated in
DataHour: Text Pre-processing using NLTK and Python
|
Participated in
DataHour: Methods for Explaining the Blackbox of Machine Learning Model
|
Participated in
DataHour: Introduction to Interpretable Machine Learning
|
Participated in
DataHour: Building NLP applications using Hugging Face
|
Participated in
DataHour: An Introduction and Hands-On to Named Entity Recognition
|
Participated in
Learn to Build an Artificial Intelligence Model with Kaggle Grandmasters
|
Participated in
DataHour: Hands-on with Social Network Analysis
|
Participated in
DataHour: Introduction to Optimization Problems for Data Scientists
|
Participated in
DataHour: Hands-on with Data Analysis Expressions(DAX) for Power BI
|
Participated in
DataHour: Deep Learning - Maths Behind Back-Propagation
|
Participated in
DataHour: Exploring the Best Book Sellers Dataset
|
Participated in
DataHour: Everything you need to know about Speech Recognition
|
Participated in
DataHour: Feature Engineering on Images using Convolutional Neural Networks(CNN)
|
Participated in
DataHour: Building AI Applications in Minutes
|
Participated in
DataHour: MLOps—DevOps for Machine Learning
|
Participated in
DataHour: Real-world Applications of Data science
|
Participated in
DataHour: Bias and Fairness in NLP
|
Participated in
DataHour: Next Leap - Data Science Adoption to Application
|
Participated in
DataHour: Understanding Search Query
|
Participated in
DataHour: Smart Machine Learning Solution Based on Ontology and Knowledge Graph
|
Participated in
DataHour: Computer Vision Landscape
|
Participated in
DataHour: Making Sense of Clinical Text Data at Scale with NLP
|
Participated in
DataHour: Analyzing Movie Data using MongoDB
|
Participated in
DataHour: Designing an end-to-end Neural Search Pipeline with Similarity Learning
|
Participated in
DataHour: Data Visualization using Python
|
Participated in
DataHour: Understanding AWS Virtual Private Cloud(VPC) Concepts
|
Participated in
DataHour: Introduction to Explainable AI (XAI)
|
Participated in
DataHour: Leveraging GCP Vertex AI for Machine Learning
|
Participated in
DataHour: Quantum Computing Simulator Acceleration
|
Participated in
DataHour: Stirring up Data Science with SQL
|
Participated in
DataHour: Prediction to Production in Machine Learning
|
Participated in
DataHour: Trees of Data Science
|
Participated in
DataHour: Dynamic Time Warping for Time Series Classification
|
Participated in
DataHour: Deep Dive into Practical Machine Learning with Career Insights
|
Participated in
DataHour: Data Operations on Azure
|
Participated in
DataHour: Jumpstart your Career with AWS AI/ML
|
Participated in
DataHour: Nirvana State of MLOps
|
Participated in
DataHour: Introduction to GAN - A Practical Approach
|
Participated in
DataHour: Product Oriented Data Scientists
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Participated in
DataHour: Key steps for Designing Deep Neural Network and its scope in Industry
|
Participated in
DataHour: Anomaly detection using NLP and Predictive Modeling
|
Participated in
DataHour: Data Science in Retail
|
Participated in
DataHour: Data Science Data management using Pandas
|
Participated in
DataHour: Mitigating Bias in Machine Learning
|
Participated in
DataHour: Google Cloud AI/ML
|
Participated in
DataHour: Forecasting Stories
|
Participated in
DataHour: Energy Data Science - Project From Scratch
|
Participated in
DataHour: Getting Started with EDA tools - Numpy and Pandas
|
Participated in
DataHour: Explainable AI - Need and Implementation
|
Participated in
DataHour: Practical Applications of Data science in Ecommerce
|
Participated in
DataHour: The Fundamentals of Quantum Computing
|
Participated in
DataHour: How to tackle Overfitting?
|
Participated in
DataHour: Sentiment Analysis from Scratch!
|
Participated in
DataHour: Hands-on with A/B Testing
|
Participated in
DataHour: Key steps for Designing Artificial Neural Network (ANN) for Image classification
|
Participated in
DataHour: Building Data Pipelines on GCP
|
Participated in
DataHour: Modern Deep Learning Architecture
|
Participated in
DataHour: 5 things you should know about Azure SQL
|
Participated in
DataHour: Prediction to Production in Machine Learning
|
Participated in
DataHour: Everything You Need to Know About Numpy
|
Participated in
DataHour: Using Word & Document Embeddings for Sentiment Analysis
|
Participated in
DataHour: AI & ML in the Automotive Industry
|
Participated in
DataHour: Topic Modeling using Transformer Based Embeddings
|
Participated in
DataHour: ETL Pipelines in GCP
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Participated in
DataHour: Knowledge Graph Solutions using Neo4j
|
Participated in
DataHour: Practical Time Series Analysis
|
Participated in
DataHour: Building Machine Learning Models in BigQuery
|
Participated in
DataHour: Key steps for Designing Convolutional Neural Network(CNN) for Image Classification
|
Participated in
DataHour: An Introduction to Central Limit Theorem
|
Participated in
DataHour: DCNN for Machine RUL Prediction using Time-series Data
|
Participated in
DataHour: A Day in the Life of a Data Scientist
|
Participated in
DataHour: Classification ML Model from Scratch
|
Participated in
DataHour: NLP aspects in Telecommunication Industry
|
Participated in
DataHour: Intelligent Knowledge Mining with Azure NLP and Graph databases
|
Participated in
DataHour: Visualizing Data using Python
|
Participated in
DataHour: Getting Started with AWS EC2
|
Participated in
DataHour: Model Guesstimation (MLOps)
|
Participated in
DataHour: An Unsupervised ML approach using Clustering
|
Participated in
DataHour: ML Model Interpretation and Evaluation
|
Participated in
DataHour: M in ML stands for Math & Magic
|
Participated in
DataHour: Model Parameters vs Hyperparameters - Techniques in ML Engineering
|
Participated in
DataHour: Customizing Large Language Models GPT3 for Real-life Use Cases
|
Participated in
DataHour: Introduction to Federated Learning
|
Participated in
DataHour: ChatGPT and the coming Generative AI Revolution
|
Participated in
DataHour: Extracting Value from Data
|
Participated in
DataHour: Ensemble Techniques in Machine Learning
|
Participated in
DataHour: Unfolding Model Evaluation Metrics in Machine Learning
|
Participated in
DataHour: From Unstructured Text to Insights - Topic Modeling in NLP using LDA
|
Participated in
DataHour: Introduction to Classification using Azure Machine Learning
|
Participated in
DataHour: Hypothesis Testing A-Z
|
Participated in
DataHour: How to Approach an ML Problem Statement from Scratch
|
Participated in
DataHour: Netflix Data Analysis using Python
|
Participated in
DataHour: The Art of Feature Engineering
|
Participated in
DataHour: Exploratory Data Analysis with F#
|
Participated in
DataHour: Causal Experimentations - When A/B Test is Not Possible
|
Participated in
DataHour: Introduction to Positive Unlabelled(PU) Learning
|
Participated in
DataHour: Document Understanding and OCR using Transformers
|
Participated in
DataHour: Introduction and Hands-on workshop with Reinforcement Learning
|
Participated in
DataHour: Need for Self Supervised Learning - Practice at SAP
|
Participated in
DataHour: Practical Hypothesis Testing
|
Participated in
DataHour: Steps before using an ML Model
|
Participated in
DataHour: Statistics in Data Science
|
Participated in
DataHour: Understanding Dimensionality Reduction
|
Participated in
DataHour: HIV Analysis using ML and Flutter
|
Participated in
DataHour: Python Data Structures
|
Participated in
DataHour: Application of ChatGPT and DALL-E
|
Participated in
DataHour: Exploring Heart Disease Data using Python
|
Participated in
DataHour: Evaluation Measures for Binary Classification
|
Participated in
DataHour: Natural Language Processing for Indian Languages
|
Participated in
DataHour: Transformer Architecture and its Applications
|
Participated in
DataHour: NLP Interaction with Power BI
|
Participated in
DataHour: Distinguishing Bot Text From Human Text Corpus
|
Participated in
DataHour: Building and Operationalizing an Explainable Predictive Model
|
Participated in
DataHour: Demystifying Clustering in Topic Modeling Algorithms like BERTopic
|
Participated in
DataHour: How do Algorithms Generate Recommendations?
|
Participated in
DataHour: Classification Algorithms Evaluation Metrics
|
Participated in
DataHour: Advanced Exploratory Data Analysis on Credit Data
|
Participated in
DataHour: Conversational AI and its Uses
|
Participated in
DataHour: Exploring Multi-label & Multi-class Classification
|
Participated in
DataHour: Normal Distribution - Understanding the Numbers and its Real Life Applications
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Participated in
DataHour: Train GPT2 on Indian Language Dataset
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Participated in
DataHour: Diabetes Prediction Using Survival Analysis
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Participated in
DataHour: Machine Learning Model Development using Pandas, Numpy and Scikit-Learn
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Participated in
DataHour: Analyzing Loan Application Data using Python
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Participated in
DataHour: Hyperparameter Optimization Demystified
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Participated in
DataHour: An Introduction to Natural Language Processing
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Participated in
DataHour: Introduction to Optimization using Genetic Algorithms
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Participated in
DataHour: Understanding Logistic Regression
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Participated in
DataHour: Anomaly Detection in Time Series Data
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Participated in
DataHour: Real-time Machine Learning - Challenges and Solution
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Participated in
DataHour: Experiments with Interpretable Artificial Intelligence
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Participated in
DataHour: Basic Concepts of Object Oriented Programming in Python
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