| Participated in Skilltest: Image Processing and secured rank 111 |
| Participated in SVM Skilltest and secured rank 68 |
| Participated in Skilltest: k-Nearest Neighbor (kNN) and secured rank 277 |
| 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: 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: 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: Generating Labeled Data through Weak Supervision |
| Participated in DataHour: Google Cloud Vertex AI Platform |
| Participated in DataHour: Apache Airflow - An Open Source Workflow Manager |
| Participated in DataHour: Data Availability Through Data Lake in Large Organization |
| Participated in DataHour: Feature Engineering and Selection for Machine Learning |
| Participated in DataHour: Best of Pandas & The Power of Simple Models |
| Participated in DataHour: Conversational Intelligence & Interactive Bots |
| Participated in DataHour: Caching in Data Science |
| Participated in DataHour: Transformers from Scratch |
| Participated in DataHour: Machine Learning on Live Streaming Data for AIOps |
| Participated in DataHour: Evaluation Criteria for Validating Machine Learning Models |
| Participated in DataHour: Dataflow on Google Cloud |
| 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 |
| Participated in DataHour: How Companies Use SQL to Extract Meaningful Insights Through Data? |
| Participated in DataHour: Feature Engineering and benefits of EDA |
| Participated in DataHour: Constructing Machine Learning Pipelines using Scikit-learn |
| Participated in DataHour: Analyzing Data with SQL |
| Participated in DataHour: Building a Web Application using Flask |
| Participated in DataHour: Google Cloud No Code/Low Code AI Solutions |
| Participated in DataHour: Roadmap to Data Engineering for Beginners |
| Participated in DataHour: Data Architect vs Data Engineer |
| 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 |
| Participated in DataHour: Everything You Need to Know About Pandas |
| Participated in DataHour: Building Effective Data Pipelines |
| Participated in DataHour: Text Classification for Beginners |
| Participated in DataHour: Deep Dive into Airflow Components |
| Participated in DataHour: Exploring the Best Book Sellers Dataset |
| Participated in DataHour: Data Preparation and Feature Engineering in ML |
| Participated in DataHour: Unlocking the Power of Embeddings |
| Participated in DataHour: An Introduction to Spark for Data Engineering |
| Participated in DataHour: Optimizing Real-Time ML Inference with Nvidia Triton Inference Server |
| Participated in DataHour: A/B testing - Theory, Practice and Pitfalls |
| Participated in DataHour: Understanding Graph Data Science |
| 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: Making Data Pipelines Easy with Dataproc and Composer |
| 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 DataHour: Introduction to Docker |
| Participated in DataHour: Data Engineering - Tools and Techniques |
| Participated in DataHour: Build Apache Nifi using Serverless Cloud Infrastructure |
| Participated in DataHour: Data Engineering in a Nutshell |
| Participated in Twitter Sentiment Analysis |
| Participated in Identify the Digits (MNIST) |
| Participated in Age Detection of Actors |
| Participated in Practice Problem: Skilltest - Machine Learning |
| Participated in Click Prediction Hackathon |
| Participated in Experiments with Data |
| Participated in Black Friday Sales Prediction |
| Participated in Loan Prediction |
| Participated in Skilltest: Tree Based Models |
| Participated in Practice Problem: Urban Sound Classification |
| Participated in Time Series Forecasting |
| Participated in Online Challenge: Build A Recommendation Engine (Powered by IBM Cloud) |
| Participated in Big Mart Sales Prediction |
| Participated in DataHour: Data to Insightful Actions with No Code AI |
| Participated in DataHour: Deep Dive into Graph Neural Nets for Content NLP |
| Participated in DataHour: Methods for Explaining the Blackbox of Machine Learning Model |
| Participated in DataHour: Data Modeling Concepts |
| Participated in DataHour: Text Pre-processing using NLTK and Python |
| Participated in DataHour: Distinguishing Bot Text From Human Text Corpus |
| Participated in DataHour: Sentiment Analysis from Scratch! |
| Participated in DataHour: An Introduction to AWS EMR |
| Participated in DataHour: Everything You Need to Know About Numpy |
| Participated in DataHour: Introduction To BigQuery ML |
| Participated in DataHour: Using Word & Document Embeddings for Sentiment Analysis |
| Participated in DataHour: Topic Modeling using Transformer Based Embeddings |
| Participated in DataHour: Getting Started with Big Data |
| Participated in DataHour: An Introduction to Central Limit Theorem |
| Participated in DataHour: ML Model Interpretation and Evaluation |
| Participated in DataHour: ChatGPT and the coming Generative AI Revolution |
| Participated in DataHour: Unfolding Model Evaluation Metrics in Machine Learning |
| Participated in DataHour: Netflix Data Analysis using Python |
| Participated in DataHour: Data Warehouse and its importance in Data World |
| Participated in DataHour: HIV Analysis using ML and Flutter |
| Participated in DataHour: Predicting Road Quality using AI - An MLOps Demo Pipeline |
| 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: SQL - Intermediate to Advanced |
| Participated in DataHour: Big Data Architecture and the Best Practices on AWS |
| Participated in DataHour: Transformer Architecture and its Applications |
| Participated in DataHour: NLP Interaction with Power BI |
| Participated in DataHour: Introduction to Dimensional Data Modelling |
| Participated in DataHour: Advance SQL - Analytics/Windows Functions |
| 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 |
| Participated in DataHour: Train GPT2 on Indian Language Dataset |
| Participated in DataHour: Cloud Dataproc - Migrate and Optimize Spark Workloads |
| Participated in DataHour: Building Cloud Native Data Pipelines |
| Participated in DataHour: Diabetes Prediction Using Survival Analysis |
| Participated in DataHour: Data Modelling Demystified |
| Participated in DataHour: Machine Learning Model Development using Pandas, Numpy and Scikit-Learn |
| Participated in DataHour: Analyzing Loan Application Data using Python |
| Participated in DataHour: Hyperparameter Optimization Demystified |
| Participated in DataHour: Get Started with Hadoop |
| Participated in DataHour: An Introduction to Apache Airflow |
| Participated in DataHour: An Introduction to Natural Language Processing |
| Participated in DataHour: Introduction to Optimization using Genetic Algorithms |
| Participated in DataHour: Understanding Logistic Regression |
| Participated in DataHour: Anomaly Detection in Time Series Data |
| Participated in DataHour: Real-time Machine Learning - Challenges and Solution |
| Participated in DataHour: An Introduction to Big Data Processing using Apache Spark |
| Participated in DataHour: Google BigQuery - The Modern Cloud Data Warehouse |
| Participated in DataHour: Experiments with Interpretable Artificial Intelligence |
| Participated in DataHour: Basic Concepts of Object Oriented Programming in Python |
