Introducing
Amar Ladva
Dedicated and analytically skilled professional with a Master's degree in Artificial Intelligence and Data Analytics. Solid foundation in developing predictive models and analysing large datasets. Experienced in using various data mining algorithms and methods to extract meaningful insights from structured and unstructured data sources. Exceptional skills in developing and deploying machine learning models, optimising pipelines, and collaborating with cross functional teams to drive business growth.
Python & SQL
Data Visualisation
Statistical Analysis
Machine Learning
My Skills
What Can I Do? 👨💻
As a data scientist, I excel in Python, statistics, and data visualisation, leveraging these to uncover and communicate insights from data. Proficient in project and database management, I also focus on continuous learning in big data technologies and research methodologies. My approach combines technical proficiency with collaboration, driving advancements in business development through innovative data analysis and interpretation.
Project 1
Football Player Valuation⚽
In this research project, I delve into the intricacies of football player valuation, examining how performance metrics, alongside non-performance factors like age, nationality, and height, influence market value. Utilising the comprehensive WyScout database, I applied neural networks to accurately predict players' positions based on their performance data. This exploration sheds new light on the multifaceted elements that determine a player's market worth, offering a deeper understanding of valuation in the football realm.
Project 2
Movie Recommender System 🎥
Discover the power of personalised movie recommendations! This Python project harnesses the MovieLens dataset to build a collaborative filtering-based recommender system. By analysing user ratings and movie similarities, it predicts ratings for unwatched films and generates tailored suggestions. Dive into the code to uncover the magic behind finding your next favourite movie!
Project 3
Predicting Football Positions From Heatmaps With CNNs ⚽
This project employs a Convolutional Neural Network (CNN) to interpret football players' movement heatmaps scraped from SofaScore. By analysing these spatial data patterns, the model adeptly predicts players' field positions, combining data scraping and machine learning for enhanced football strategy and performance analytics.
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Jared Warner
CEO of Figma
The quick, brown fox jumps over a lazy dog. DJs flock by when MTV ax quiz prog. Junk MTV quiz graced by fox whelps. Bawds jog, flick quartz, vex nymphs. Waltz, bad nymph, for quick jigs vex!
Amman Payne
CEO of Figma