Participated in Skilltest: Deep Learning and secured rank 136 |
Participated in Skilltest: Logistic Regression and secured rank 288 |
Participated in Skilltest: Tree Based Models and secured rank 162 |
Participated in SVM Skilltest and secured rank 196 |
Participated in DataHour: Evaluating LLMs and LLM Systems : Pragmatic Approach |
Participated in DataHour: Continuous Testing and Evaluation with LLMs |
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 DataHour: Harnessing ML and NLP for Elevated Customer Experiences |
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 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 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 DataHour: Demystifying Demand Forecasting for Retail Success |
Participated in DataHour: LLM Training Tips & Tricks |
Participated in DataHour: Unwritten Rules for Success in Machine Learning |
Participated in DataHour: Why Did My AI Do That? Decoding Decision-Making in ML |
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: Machine Learning Tips and Tricks |
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 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: From APIs to Insights: Building Custom Power BI Connectors for RESTful APIs |
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 DataHour: Generative AI using Azure Open AI |
Participated in DataHour: Generative AI - Midjourney, Code Generation & Beyond |
Participated in DataHour: Reducing chatGPT Hallucinations by 80% |
Participated in DataHour: Building Bridges - The Art of Prompt Engineering |
Participated in DataHour: LlamaIndex - QA Systems with Private Data and Effective Evaluation |
Participated in DataHour: Handling Satellite and Geospatial Raster Data in Python |
Participated in DataHour: Titanic Machine Learning Case Study using Python |
Participated in DataHour: Statistics with Python for Data Science |
Participated in DataHour: ChatGPT in Python for Beginners |
Participated in DataHour: From Pixels to Insights- Practical Hands-on with Convolutional Neural Networks |
Participated in DataHour: An Overview of Generative AI |
Participated in DataHour: Exploring Dimensionality Reduction |
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 |
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: Deep Dive into Kubernetes and Concepts of Containerization |
Participated in DataHour: An Introduction to Machine Learning with Sequence Data |
Participated in DataHour: FIFA World Cup Match Analysis Using Python |
Participated in DataHour: Basics of Big Data File Formats |
Participated in DataHour: Getting Started with Python |
Participated in DataHour: Implementing Gradient Descent in Python |
Participated in DataHour: Generating Labeled Data through Weak Supervision |
Participated in DataHour: Google Cloud Vertex AI Platform |
Participated in DataHour: Hands-on Journey to Neural Networks |
Participated in DataHour: Apache Airflow - An Open Source Workflow Manager |
Participated in DataHour: Data Availability Through Data Lake in Large Organization |
Participated in DataHour: How to Build a Multi Task Model using TensorFlow |
Participated in DataHour: Feature Engineering and Selection for Machine Learning |
Participated in DataHour: Deep Learning for Time Series Forecasting |
Participated in DataHour: Best of Pandas & The Power of Simple Models |
Participated in DataHour: Conversational Intelligence & Interactive Bots |
Participated in DataHour: Data Architect vs Data Engineer |
Participated in DataHour: Contrastive Learning for Image Classification |
Participated in DataHour: Feature Engineering and benefits of EDA |
Participated in DataHour: Analyzing Data with SQL |
Participated in DataHour: Evaluation Criteria for Validating Machine Learning Models |
Participated in DataHour: Constructing Machine Learning Pipelines using Scikit-learn |
Participated in DataHour: Forecasting & Time-series Analysis |
Participated in DataHour: How Companies Use SQL to Extract Meaningful Insights Through Data? |
Participated in DataHour: Caching in Data Science |
Participated in DataHour: Dataflow on Google Cloud |
Participated in DataHour: Machine Learning on Live Streaming Data for AIOps |
Participated in DataHour: Transforming HR with People Analytics |
Participated in DataHour: Transformers from Scratch |
Participated in DataHour: A Simple Guide to Deep Metric Learning |
Participated in DataHour: Boosting Performance with Ensemble Methods |
Participated in DataHour: Document Segmentation using Layout Parser |
Participated in DataHour: Building a Web Application using Flask |
Participated in DataHour: The Art of Using GPT3 Power |
Participated in DataHour: An Introduction to POS Tagging and Hidden Markov Model |
Participated in Twitter Sentiment Analysis |
Participated in Recommendation Engine |
Participated in AV LearnUp Mumbai: HR Analytics |
Participated in Experiments With Data |
Participated in Skilltest: Statistics |
Participated in Skilltest: Statistics II |
Participated in Experiments with Data |
Participated in MiniHack: Machine Learning |
Participated in #AVdatafest Launch Party & Panel Discussion |
Participated in #AVdatafest Rampaging DataHulk: Machine Learning Mini-Hack |
Participated in Skilltest: Linear Regression |
Participated in Re-Date Your Data: Learning Contest |
Participated in Practice Problem: Strategic Thinking II |
Participated in Experiments With Data |
Participated in The Strategic Monk |
Participated in Data Science Interview Preparation Test |
Participated in Strategic Sprint Mar 2017 |
Participated in Skilltest: Ensemble Modeling |
Participated in Webinar: Future of Big Data & Career Opportunities in Big Data World |
Participated in Webinar on Information retrieval from unstructured text at scale using advanced deep learning |
Participated in Identify the Digits (MNIST) |
Participated in Experiments With Data |
Participated in The Smart Recruits |
Participated in Mind Your Strategy |
Participated in Skilltest : R for Data Science |
Participated in Black Friday Sales Prediction |
Participated in Skilltest: Machine Learning |
Participated in Skilltest: Clustering |
Participated in Skilltest: SQL |
Participated in AV LearnUp Mumbai: Marketing Analytics in Banking & Finance |
Participated in Date Your Data |
Participated in Skilltest: Deep Learning |
Participated in The Strategic Ball |
Participated in Skilltest: SAS |
Participated in Operations Research: Big Buck Challenge by IEOR @ IITB & McKinsey Knowledge Center India |
Participated in MLWARE 1 - Text Mining Challenge |
Participated in Data Science Hackathon - Cross-sell: target the right customer |
Participated in Webinar: How to Get Started with Natural Language Processing (NLP) |
Participated in Online Challenge: Build A Recommendation Engine (Powered by IBM Cloud) |
Participated in Identify the apparels (Fashion MNIST) |
Participated in Practice Problem: Intel Scene Classification Challenge |
Participated in Practice Problem: Urban Sound Classification |
Participated in McKinsey Analytics Online Hackathon- Recommendation Design |
Participated in McKinsey Analytics Online Hackathon - Sales Excellence |
Participated in Fractal Analytics Hiring Hackathon |
Participated in Face Counting Challenge |
Participated in JanataHack: Mobility Analytics |
Participated in Webinar: Build a Recommendation Engine for Retail Data |
Participated in Loan Prediction |
Participated in Webinar: Problem Solving using AI - The QuantumBlack Story |
Participated in AmExpert 2018 (Machine Learning Hackathon) |
Participated in JanataHack: Machine Learning for IoT |
Participated in Age Detection of Actors |
Participated in Data Science Hackathon: Churn Prediction |
Participated in Practice Problem: Skilltest - Machine Learning |
Participated in Webinar: How to Deploy your ML Model? |
Participated in Webinar: Going Beyond your First ML Project |
Participated in Webinar: Business Analytics Vs Data Science |
Participated in WEBINAR: The Importance Of Building The Right Problem Statement In Data Science |
Participated in Janatahack: Healthcare Analytics II |
Participated in JanataHack: Time Series Forecasting |
Participated in Time Series Forecasting |
Participated in JanataHack: HR Analytics |
Participated in JanataHack: Machine Learning for Banking |
Participated in LTFS Data Science FinHack 3 |
Participated in Janatahack: Healthcare Analytics |
Participated in JanataHack: Recommendation Systems |
Participated in Janatahack: Customer Segmentation |
Participated in Janatahack: Machine Learning in Agriculture |
Participated in JanataHack: Demand Forecasting |
Participated in Janatahack: Independence Day 2020 ML Hackathon |
Participated in Janatahack: Cross-sell Prediction |
Participated in HR Analytics |
Participated in Big Mart Sales Prediction |