Prudhvi

Prudhvi Badri

Hackathons
35
Rank
174
Points
Participated in Game of Deep Learning: Computer Vision Hackathon
Participated in JanataHack: HR Analytics
Participated in JanataHack: Mobility Analytics
Participated in JanataHack: NLP Hackathon
Participated in WNS Analytics Wizard 2019
Participated in Club Mahindra DataOlympics
Participated in JanataHack - E-Commerce Analytics ML Hackathon
Participated in LTFS Data Science FinHack ( ML Hackathon)
Participated in LTFS Data Science FinHack 2
Participated in India ML Hiring Hackathon 2019
Participated in AmExpert 2019 – Machine Learning Hackathon
Participated in Dataverse Hack
Participated in Webinar: How to crack Big Data & Data Science Role?
Participated in Skilltest: Deep Learning
Participated in Skilltest: Machine Learning
Participated in The Strategic Monk
Participated in Skilltest: SQL
Participated in Skilltest: Clustering
Participated in Data Science Hackathon: Churn Prediction
Participated in Skilltest: Ensemble Modeling
Participated in Big Mart Sales Prediction
Participated in Twitter Sentiment Analysis
Participated in Skilltest: Tree Based Algorithms
Participated in The Strategic Ball
Participated in Practice Problem: Intel Scene Classification Challenge
Participated in Black Friday Sales Prediction
Participated in JanataHack: Time Series Forecasting
Participated in Face Counting Challenge
Participated in QuantumBlack Hackathon
Participated in Online Challenge: Build A Recommendation Engine (Powered by IBM Cloud)
Participated in Recommendation Engine
Participated in Skilltest: Regression
Participated in Practice Problem: Strategic Thinking II
Participated in Food Demand Forecasting
Participated in The Strategic Saviour
Participated in Age Detection of Actors
Participated in Identify the Digits (MNIST)
Participated in Practice Problem: Urban Sound Classification
Participated in Identify the apparels (Fashion MNIST)
Participated in HR Analytics
Participated in Time Series Forecasting
Participated in Experiments with Data
Participated in #AVdatafest PowerTool: R for Data Science
Participated in Identify the Sentiments
Participated in Predict Number of Upvotes
Participated in Janata Hack - Machine Learning Hackathon to support Janata Curfew
Participated in JanataHack: Recommendation Systems
Participated in JanataHack: Machine Learning for Banking
Participated in Loan Prediction
Participated in JanataHack: Demand Forecasting
Participated in JanataHack: Machine Learning for IoT
Participated in Janatahack: Customer Segmentation
Participated in Janatahack: Healthcare Analytics
Participated in Janatahack: Machine Learning in Agriculture
Participated in HackLive - Guided Community Hackathon!
Participated in DataHour: Think like a Data Scientist
Participated in Panel Discussion: How to Ace DS Competitions?
Participated in DataHour: Introduction to Data-driven Decisions
Participated in DataHour: Effective Feature Engineering for Building Better Models
Participated in DataHour: An Overview of Feature Engineering for Data Science
Participated in DataHour: Efficient Implementations of Transformers
Participated in DataHour: Introduction to Optimization Problems for Data Scientists
Participated in DataHour: MLOps—DevOps for Machine Learning
Participated in DataHour: SQL- One of the Key Ingredients for Data Science
Participated in DataHour: ML oops to MLOps!
Participated in DataHour: Deploying Deep Learning model to production using FastAPI & Docker
Participated in DataHour: Next Leap - Data Science Adoption to Application
Participated in DataHour: Introduction to Network Science
Participated in DataHour: Understanding AWS Virtual Private Cloud(VPC) Concepts
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: 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
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: Explainable AI - Need and Implementation
Participated in DataHour: Getting Started with EDA tools - Numpy and Pandas
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: 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: AI & ML in the Automotive Industry
Participated in DataHour: ETL Pipelines in GCP
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: 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: 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: Extracting Value from Data
Participated in DataHour: Convolution Neural Network for Image Recognition
Participated in DataHour: Ensemble Techniques 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: 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 Dataverse Hack: Build an AI Model to Save Lives

Experience