prajyot

prajyot

Hackathons
7038
Rank
0
Points
Participated in Skilltest: Tree Based Models
Participated in SVM Skilltest
Participated in Skilltest: k-Nearest Neighbor (kNN)
Participated in Skilltest: Image Processing
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 Twitter Sentiment Analysis
Participated in Loan Prediction
Participated in Identify the Digits (MNIST)
Participated in Time Series Forecasting
Participated in Big Mart Sales Prediction
Participated in Experiments with Data
Participated in Data Science Interview Preparation Test
Participated in Age Detection of Actors
Participated in Practice Problem: Skilltest - Machine Learning
Participated in Click Prediction Hackathon
Participated in Student DataFest 2018: The Data Identity
Participated in Recommendation Engine
Participated in Black Friday Sales Prediction
Participated in DataHour: Data to Insightful Actions with No Code AI
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: An Introduction to Central Limit Theorem
Participated in DataHour: ML Model Interpretation and Evaluation
Participated in DataHour: Extracting Value from Data
Participated in DataHour: Introduction to Federated Learning
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: Netflix Data Analysis using Python
Participated in DataHour: The Art of Feature Engineering
Participated in DataHour: Exploratory Data Analysis with F#
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: 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: 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 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

Experience

Education

Course Any other Degree
University Shivaji University, kolhapur
Duration None - 2015
Job Profile
Course Any other Degree
University Savitribai phule Pune University
Duration None - Present
Job Profile

Skill

excel