skds

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About skds

Member Since Sept. 3, 2015, 6:19 p.m.
Location Hyderabad
Area of Interest R, MATLAB, OCTAVE, MINITAB

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Participated in The Strategic Saviour and secured rank 338
Participated in The D Hack and secured rank 75
Participated in DataHour: Continuous Testing and Evaluation with LLMs
Participated in DataHour: Harnessing ML and NLP for Elevated Customer Experiences
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 Machine Learning Huddle: Hyderabad Meet-Up
Participated in Lord of the Machines: Data Science Hackathon
Participated in DataHack Premier League 2018
Participated in The Smart Recruits
Participated in The Strategic Monk
Participated in Skilltest: Machine Learning
Participated in Mind Your Strategy
Participated in Black Friday Data Hack
Participated in McKinsey Analytics Online Hackathon
Participated in DataHour: Hyperparameter Optimization 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: Diabetes Prediction Using Survival Analysis
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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