Data Science | Kaggle

Jan 1, 2016
Kaggle
Neural Networks, Image Source, tds

Bike Sharing

  • Forecast bike rental demand, Kaggle
    • Performed variable manipulation using data visualisation techniques and correlation matrix as preparatory steps for model construction
    • Trained a random forest classifier on the significant parameters & performed hyper-parameter tuning to achieve the error score of 0.4

Titanic

  • Prediction of likelihood of survival of passengers, Kaggle
    • Developed insights on correlations and significant variables for prediction of survival of passengers after preprocessing the training data. Applied regression model and machine learning algorithms (SVM and Random forest) to achieve the maximum accuracy of 78.5
Independent Rocket Propulsion Ramjet Engines Igniter
Manu Lahariya
Manu Lahariya
मनु लहरिया
AI Scientist, Amsterdam
PhD, Artificial Intelligence, AI4E, IDLab

My research interests include physics based machine learning, reinforcement learning and deep learning.