ashokasr143

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About ashokasr143

Member Since July 14, 2017, 11:44 a.m.
Location bangalore
Area of Interest R, Python, Machine Learning, Statistics, Predictive modelling

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Participated in WNS Analytics Wizard 2018 (Machine Learning Hackathon) and secured rank 1214
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: Building Generative AI Applications using Amazon Bedrock
Participated in DataHour: Natural Language to SQL Translation: The Challenges, Evolution and Future
Participated in DataHour:LangChain 101
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: Search With ChatGPT: RAG and Semantic Search
Participated in DataHour: Creating Synthetic Data: An Easy Python Tutorial for Beginners
Participated in DataHour: Natural Language to SQL: Analyzing Netflix Movies with LLMs
Participated in DataHour: Mastering Conversational AI: Building Question-Answer Bot with LLM and RAG
Participated in DataHour: Demystifying Demand Forecasting for Retail Success
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: Machine Learning Tips and Tricks
Participated in DataHour: From APIs to Insights: Building Custom Power BI Connectors for RESTful APIs
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: Exploring Dimensionality Reduction
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: Generating Labeled Data through Weak Supervision
Participated in DataHour: Feature Engineering and Selection for Machine Learning
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: 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: 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: 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: 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 WEBINAR: The Importance Of Building The Right Problem Statement In Data Science
Participated in Data Hack Round 1: Online Quiz (Nirvahana, By iQ’oniQ, NMIMS Hyderabad)
Participated in Data Science Interview Preparation Test
Participated in HR Analytics and secured rank 1214
Participated in AV LearnUp Bengaluru: Data Science in Healthcare
Participated in Practice Problem: Urban Sound Classification
Participated in Big Mart Sales Prediction
Participated in Identify the Digits (MNIST)
Participated in Black Friday Sales Prediction
Participated in AV LearnUp Bengaluru : Data Science in Finance
Participated in The Bots Are Here (Bengaluru Meetup)
Participated in Webinar: How to crack analytics and machine learning interviews at campus placements?
Participated in [Student DataFest 2018] Skilltest - Intro to Machine Learning
Participated in Time Series Forecasting
Participated in Loan Prediction
Participated in McKinsey Analytics Online Hackathon
Participated in Identify the Sentiments
Participated in JanataHack: Mobility Analytics
Participated in JanataHack: Machine Learning for IoT
Participated in JanataHack: NLP Hackathon
Participated in Twitter Sentiment Analysis
Participated in JanataHack: Recommendation Systems
Participated in Janatahack: Cross-sell Prediction
Participated in Analytics Vidhya Hiring Hackathon
Participated in Experiments with Data
Participated in Lord of the Machines: Data Science Hackathon
Participated in Machine Learning at Scale to Power Businesses (Bengaluru Meetup)
Participated in JanataHack: Time Series Forecasting
Participated in JanataHack: HR Analytics
Participated in Janatahack: Healthcare Analytics II
Participated in JanataHack: Machine Learning for Banking
Participated in Webinar: Storytelling using Visualizations
Participated in Janatahack: Customer Segmentation
Participated in JanataHack: Demand Forecasting
Participated in Janatahack: Healthcare Analytics
Participated in Janatahack: Machine Learning in Agriculture
Participated in Janatahack: Independence Day 2020 ML Hackathon
Participated in Webinar: Need of Industry Exposure in learning and applying the practical aspects of Data Science
Participated in LTFS Data Science FinHack 3
Participated in JOB-A-THON - May 2021
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: Real-time Machine Learning - Challenges and Solution
Participated in DataHour: Experiments with Interpretable Artificial Intelligence
Participated in DataHour: Basic Concepts of Object Oriented Programming in Python
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