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 LangChain in Action: Crafting Innovative LLM Powered Applications |
Participated in AMA: Generative AI & Career in Data Science / Data Analytics |
Participated in DataHour: Introduction to LLMs: An Interactive Workshop |
Participated in GANs- Explore the Boundaries of Generative Art |
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: From Pixels to Insights- Practical Hands-on with Convolutional Neural Networks |
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: How to Start Your Career in Data Engineering with SQL and Python? |
Participated in DataHour: How to Become an AI/ML Cloud Architect? |
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: Fine Tuning NLP Pipeline on Hugging Face |
Participated in DataHour: An Overview of Named Entity Recognition(NER) |
Participated in DataHour: What do Hiring Managers Look for in Data Scientists? |
Participated in DataHour: Web Scraping using Python Libraries |
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: Implementing Gradient Descent in Python |
Participated in DataHour: Generating Labeled Data through Weak Supervision |
Participated in DataHour: Hands-on Journey to Neural Networks |
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: Machine Learning on Live Streaming Data for AIOps |
Participated in DataHour: Evaluation Criteria for Validating Machine Learning Models |
Participated in DataHour: Forecasting & Time-series Analysis |
Participated in DataHour: Boosting Performance with Ensemble Methods |
Participated in DataHour: Feature Engineering and benefits of EDA |
Participated in DataHour: Constructing Machine Learning Pipelines using Scikit-learn |
Participated in DataHour: Understanding Graph Data Science |
Participated in DataHour: A Simple Guide to Deep Metric Learning |
Participated in DataHour: Contrastive Learning for Image Classification |
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: Everything You Need to Know About Pandas |
Participated in DataHour: An Introduction to Vision for Robotics |
Participated in DataHour: An Overview of Computer Vision |
Participated in DataHour: Introduction to Deep Learning with FastAI |
Participated in DataHour: Exploring the Best Book Sellers Dataset |
Participated in DataHour: Demystifying RCNN Family for Object Detection |
Participated in DataHour: Data Preparation and Feature Engineering in ML |
Participated in DataHour: Unlocking the Power of Embeddings |
Participated in DataHour: Implementing a Neural Network using Pytorch |
Participated in DataHour: A/B testing - Theory, Practice and Pitfalls |
Participated in DataHour: An Introduction to Google Vision API |
Participated in DataHour: Dealing with Imbalanced Datasets in ML Classification Problems |
Participated in DataHour: Salary Analysis and Prediction Using ML |
Participated in DataHour: Understanding Stable Diffusion & Prompt Engineering |
Participated in DataHour: Data Wrangling Using Geospatial Data in Python |
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 DataHour: Image Classification using Deep Learning Models |
Participated in DataHour: Building Efficient Convolution Networks for Image Classification Tasks |
Participated in Mind Your Strategy |
Participated in Skilltest: Python for Data Science |
Participated in Skilltest: Tree Based Algorithms |
Participated in Loan Prediction |
Participated in Big Mart Sales Prediction |
Participated in #AVdatafest PowerTool: Python for Data Science |
Participated in Skilltest: NLP |
Participated in Practice Problem: Strategic Thinking II |
Participated in Skilltest: Machine Learning |
Participated in Skilltest: Regression |
Participated in Blogathon 2 |
Participated in Blogathon 3 |
Participated in Webinar on Information retrieval from unstructured text at scale using advanced deep learning |
Participated in Age Detection of Actors |
Participated in AVdatafest : Experiments With Data |
Participated in The Smart Recruits |
Participated in Black Friday Sales Prediction |
Participated in The Strategic Monk |
Participated in Blogathon |
Participated in The Convergence of BIG DATA and Machine Learning (Pune Meetup) |
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: Everything You Need to Know About Numpy |
Participated in DataHour: Time Series analysis using LSTM |
Participated in DataHour: An Introduction to Central Limit Theorem |
Participated in DataHour: ML Model Interpretation and Evaluation |
Participated in DataHour: M in ML stands for Math & Magic |
Participated in DataHour: An Unsupervised ML approach using Clustering |
Participated in DataHour: Customizing Large Language Models GPT3 for Real-life Use Cases |
Participated in DataHour: Multi-Objective Optimisation |
Participated in DataHour: Model Parameters vs Hyperparameters - Techniques in ML Engineering |
Participated in DataHour: Introduction to Federated Learning |
Participated in DataHour: Extracting Value from Data |
Participated in DataHour: Convolution Neural Network for Image Recognition |
Participated in DataHour: Ensemble Techniques in Machine Learning |
Participated in DataHour: Unfolding Model Evaluation Metrics in Machine Learning |
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: Diffusion Models for Generative Arts |
Participated in DataHour: Netflix Data Analysis using Python |
Participated in DataHour: Exploratory Data Analysis with F# |
Participated in DataHour: The Art of Feature Engineering |
Participated in DataHour: Causal Experimentations - When A/B Test is Not Possible |
Participated in DataHour: Introduction to Positive Unlabelled(PU) Learning |
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: Understanding the Basics of a Neural Network |
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: GANs Revolutionizing the World! |
Participated in DataHour: HIV Analysis using ML and Flutter |
Participated in DataHour: Python Data Structures |
Participated in DataHour: Exploring Heart Disease Data using Python |
Participated in DataHour: Evaluation Measures for Binary Classification |
Participated in DataHour: Building & Deploying Deep Learning Models for Sentiment Analysis |
Participated in DataHour: Building and Operationalizing an Explainable Predictive Model |
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: Exploring Multi-label & Multi-class Classification |
Participated in DataHour: Normal Distribution - Understanding the Numbers and its Real Life Applications |
Participated in DataHour: Diabetes Prediction Using Survival Analysis |
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: Introduction to Optimization using Genetic Algorithms |
Participated in DataHour: Understanding Logistic Regression |
Participated in DataHour: Anomaly Detection in Time Series Data |
Participated in DataHour: Exploring the Fundamentals of DeepMatch |
Participated in DataHour: YOLO Object Detection using Python |
Participated in DataHour: Real-time Machine Learning - Challenges and Solution |
Participated in DataHour: Training Your First PyTorch Model |
Participated in DataHour: Deploying Models for Sentiment Analysis on Cloud |
Participated in DataHour: Experiments with Interpretable Artificial Intelligence |
Participated in DataHour: Basic Concepts of Object Oriented Programming in Python |